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https://github.com/huggingface/datasets/pull/1139 | Add ReFreSD dataset | Looks good! It looks like it might need a rebase to pass the tests. Once you do that, should be good to go! | This PR adds the **ReFreSD dataset**.
The original data is hosted [on this github repo](https://github.com/Elbria/xling-SemDiv) and we use the `REFreSD_rationale` to expose all the data.
Need feedback on:
- I couldn't generate the dummy data. The file we download is a tsv file, but without extension, I suppose this is the problem. I'm sure there is a simple trick to make this work.
- The feature names.
- I don't know if it's better to stick to the classic `sentence1`, `sentence2` or to `sentence_en`, `sentence_fr` to be more explicit.
- There is a binary label (called `label`, no problem here), and a 3-class label called `#3_labels` in the original tsv. I changed it to `all_labels` but I'm sure there is better.
- The rationales are lists of integers, extracted as a string at first. I wonder what's the best way to treat them, any idea? Also, I couldn't manage to make a `Sequence` of `int8` but I'm sure I've missed something simple.
Thanks in advance | 23 | text: Add ReFreSD dataset
This PR adds the **ReFreSD dataset**.
The original data is hosted [on this github repo](https://github.com/Elbria/xling-SemDiv) and we use the `REFreSD_rationale` to expose all the data.
Need feedback on:
- I couldn't generate the dummy data. The file we download is a tsv file, but without extension, I suppose this is the problem. I'm sure there is a simple trick to make this work.
- The feature names.
- I don't know if it's better to stick to the classic `sentence1`, `sentence2` or to `sentence_en`, `sentence_fr` to be more explicit.
- There is a binary label (called `label`, no problem here), and a 3-class label called `#3_labels` in the original tsv. I changed it to `all_labels` but I'm sure there is better.
- The rationales are lists of integers, extracted as a string at first. I wonder what's the best way to treat them, any idea? Also, I couldn't manage to make a `Sequence` of `int8` but I'm sure I've missed something simple.
Thanks in advance
Looks good! It looks like it might need a rebase to pass the tests. Once you do that, should be good to go! | [
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https://github.com/huggingface/datasets/pull/1129 | Adding initial version of cord-19 dataset | Hi @ggdupont !
Have you had a chance to take a look at my suggestions ?
Feel free to ping me if you have questions or when you're ready for a review | Initial version only reading the metadata in CSV.
### Checklist:
- [x] Create the dataset script /datasets/my_dataset/my_dataset.py using the template
- [x] Fill the _DESCRIPTION and _CITATION variables
- [x] Implement _infos(), _split_generators() and _generate_examples()
- [x] Make sure that the BUILDER_CONFIGS class attribute is filled with the different configurations of the dataset and that the BUILDER_CONFIG_CLASS is specified if there is a custom config class.
- [x] Generate the metadata file dataset_infos.json for all configurations
- [x] Generate the dummy data dummy_data.zip files to have the dataset script tested and that they don't weigh too much (<50KB)
- [x] Add the dataset card README.md using the template and at least fill the tags
- [x] Both tests for the real data and the dummy data pass.
### TODO:
- [x] add more metadata
- [x] add full text
- [x] add pre-computed document embedding | 32 | text: Adding initial version of cord-19 dataset
Initial version only reading the metadata in CSV.
### Checklist:
- [x] Create the dataset script /datasets/my_dataset/my_dataset.py using the template
- [x] Fill the _DESCRIPTION and _CITATION variables
- [x] Implement _infos(), _split_generators() and _generate_examples()
- [x] Make sure that the BUILDER_CONFIGS class attribute is filled with the different configurations of the dataset and that the BUILDER_CONFIG_CLASS is specified if there is a custom config class.
- [x] Generate the metadata file dataset_infos.json for all configurations
- [x] Generate the dummy data dummy_data.zip files to have the dataset script tested and that they don't weigh too much (<50KB)
- [x] Add the dataset card README.md using the template and at least fill the tags
- [x] Both tests for the real data and the dummy data pass.
### TODO:
- [x] add more metadata
- [x] add full text
- [x] add pre-computed document embedding
Hi @ggdupont !
Have you had a chance to take a look at my suggestions ?
Feel free to ping me if you have questions or when you're ready for a review | [
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https://github.com/huggingface/datasets/pull/1129 | Adding initial version of cord-19 dataset | > Hi @ggdupont !
> Have you had a chance to take a look at my suggestions ?
> Feel free to ping me if you have questions or when you're ready for a review
Yes I did, just busy period (and no time on weekend right now ;-) ) | Initial version only reading the metadata in CSV.
### Checklist:
- [x] Create the dataset script /datasets/my_dataset/my_dataset.py using the template
- [x] Fill the _DESCRIPTION and _CITATION variables
- [x] Implement _infos(), _split_generators() and _generate_examples()
- [x] Make sure that the BUILDER_CONFIGS class attribute is filled with the different configurations of the dataset and that the BUILDER_CONFIG_CLASS is specified if there is a custom config class.
- [x] Generate the metadata file dataset_infos.json for all configurations
- [x] Generate the dummy data dummy_data.zip files to have the dataset script tested and that they don't weigh too much (<50KB)
- [x] Add the dataset card README.md using the template and at least fill the tags
- [x] Both tests for the real data and the dummy data pass.
### TODO:
- [x] add more metadata
- [x] add full text
- [x] add pre-computed document embedding | 50 | text: Adding initial version of cord-19 dataset
Initial version only reading the metadata in CSV.
### Checklist:
- [x] Create the dataset script /datasets/my_dataset/my_dataset.py using the template
- [x] Fill the _DESCRIPTION and _CITATION variables
- [x] Implement _infos(), _split_generators() and _generate_examples()
- [x] Make sure that the BUILDER_CONFIGS class attribute is filled with the different configurations of the dataset and that the BUILDER_CONFIG_CLASS is specified if there is a custom config class.
- [x] Generate the metadata file dataset_infos.json for all configurations
- [x] Generate the dummy data dummy_data.zip files to have the dataset script tested and that they don't weigh too much (<50KB)
- [x] Add the dataset card README.md using the template and at least fill the tags
- [x] Both tests for the real data and the dummy data pass.
### TODO:
- [x] add more metadata
- [x] add full text
- [x] add pre-computed document embedding
> Hi @ggdupont !
> Have you had a chance to take a look at my suggestions ?
> Feel free to ping me if you have questions or when you're ready for a review
Yes I did, just busy period (and no time on weekend right now ;-) ) | [
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https://github.com/huggingface/datasets/pull/1129 | Adding initial version of cord-19 dataset | Thanks !
It looks like the rebase messed up the github diff for this PR (2.000+ files changed)
Could you create another branch and another PR please ? | Initial version only reading the metadata in CSV.
### Checklist:
- [x] Create the dataset script /datasets/my_dataset/my_dataset.py using the template
- [x] Fill the _DESCRIPTION and _CITATION variables
- [x] Implement _infos(), _split_generators() and _generate_examples()
- [x] Make sure that the BUILDER_CONFIGS class attribute is filled with the different configurations of the dataset and that the BUILDER_CONFIG_CLASS is specified if there is a custom config class.
- [x] Generate the metadata file dataset_infos.json for all configurations
- [x] Generate the dummy data dummy_data.zip files to have the dataset script tested and that they don't weigh too much (<50KB)
- [x] Add the dataset card README.md using the template and at least fill the tags
- [x] Both tests for the real data and the dummy data pass.
### TODO:
- [x] add more metadata
- [x] add full text
- [x] add pre-computed document embedding | 28 | text: Adding initial version of cord-19 dataset
Initial version only reading the metadata in CSV.
### Checklist:
- [x] Create the dataset script /datasets/my_dataset/my_dataset.py using the template
- [x] Fill the _DESCRIPTION and _CITATION variables
- [x] Implement _infos(), _split_generators() and _generate_examples()
- [x] Make sure that the BUILDER_CONFIGS class attribute is filled with the different configurations of the dataset and that the BUILDER_CONFIG_CLASS is specified if there is a custom config class.
- [x] Generate the metadata file dataset_infos.json for all configurations
- [x] Generate the dummy data dummy_data.zip files to have the dataset script tested and that they don't weigh too much (<50KB)
- [x] Add the dataset card README.md using the template and at least fill the tags
- [x] Both tests for the real data and the dummy data pass.
### TODO:
- [x] add more metadata
- [x] add full text
- [x] add pre-computed document embedding
Thanks !
It looks like the rebase messed up the github diff for this PR (2.000+ files changed)
Could you create another branch and another PR please ? | [
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https://github.com/huggingface/datasets/pull/1126 | Adding babi dataset | This is ok now @lhoestq
I've included the tweak to `dummy_data` to only use the data transmitted to `_generate_examples` by default (it only do that if it can find at least one path to an existing file in the `gen_kwargs` and this can be unactivated with a flag).
Should I extract it in another PR or is it ok like this? | Adding the English version of bAbI.
Samples are taken from ParlAI for consistency with the main users at the moment.
Supersede #945 (problem with the rebase) and adresses the issues mentioned in the review (dummy data are smaller now and code comments are fixed). | 61 | text: Adding babi dataset
Adding the English version of bAbI.
Samples are taken from ParlAI for consistency with the main users at the moment.
Supersede #945 (problem with the rebase) and adresses the issues mentioned in the review (dummy data are smaller now and code comments are fixed).
This is ok now @lhoestq
I've included the tweak to `dummy_data` to only use the data transmitted to `_generate_examples` by default (it only do that if it can find at least one path to an existing file in the `gen_kwargs` and this can be unactivated with a flag).
Should I extract it in another PR or is it ok like this? | [
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https://github.com/huggingface/datasets/pull/1126 | Adding babi dataset | Nice !
Could you add the dummy data generation trick in another PR ?
I think we can also extend it to make it work not only with data files paths but also with data directories (sometimes it's one of the parent directory that is passed to gen_kwargs, not the actual path to the file).
This will help a lot to make the dummy data lighter ! | Adding the English version of bAbI.
Samples are taken from ParlAI for consistency with the main users at the moment.
Supersede #945 (problem with the rebase) and adresses the issues mentioned in the review (dummy data are smaller now and code comments are fixed). | 67 | text: Adding babi dataset
Adding the English version of bAbI.
Samples are taken from ParlAI for consistency with the main users at the moment.
Supersede #945 (problem with the rebase) and adresses the issues mentioned in the review (dummy data are smaller now and code comments are fixed).
Nice !
Could you add the dummy data generation trick in another PR ?
I think we can also extend it to make it work not only with data files paths but also with data directories (sometimes it's one of the parent directory that is passed to gen_kwargs, not the actual path to the file).
This will help a lot to make the dummy data lighter ! | [
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https://github.com/huggingface/datasets/pull/1125 | Add Urdu fake news dataset. | Hi @chaitnayabasava ! you can try rebasing and see if that fixes the number of files changed, otherwise please do open a new PR with only the relevant files and close this one :) | Added Urdu fake news dataset. More information about the dataset can be found <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>. | 34 | text: Add Urdu fake news dataset.
Added Urdu fake news dataset. More information about the dataset can be found <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>.
Hi @chaitnayabasava ! you can try rebasing and see if that fixes the number of files changed, otherwise please do open a new PR with only the relevant files and close this one :) | [
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https://github.com/huggingface/datasets/pull/1124 | Add Xitsonga Ner | looks like this PR includes changes about many files other than the ones related to xitsonga NER
could you create another branch and another PR please ? | Clean Xitsonga Ner PR | 27 | text: Add Xitsonga Ner
Clean Xitsonga Ner PR
looks like this PR includes changes about many files other than the ones related to xitsonga NER
could you create another branch and another PR please ? | [
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https://github.com/huggingface/datasets/pull/1118 | Add Tashkeela dataset | > Sorry @lhoestq for the trouble, sometime I forget to change the names :/
haha it's ok ;) | Arabic Vocalized Words Dataset. | 18 | text: Add Tashkeela dataset
Arabic Vocalized Words Dataset.
> Sorry @lhoestq for the trouble, sometime I forget to change the names :/
haha it's ok ;) | [
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https://github.com/huggingface/datasets/pull/1117 | Fix incorrect MRQA train+SQuAD URL | Thanks ! could you regenerate the dataset_infos.json file ?
```
datasets-cli test ./datasets/mrqa --save_infos --all_configs --ignore_verifications
```
also cc @VictorSanh | Fix issue #1115
| 20 | text: Fix incorrect MRQA train+SQuAD URL
Fix issue #1115
Thanks ! could you regenerate the dataset_infos.json file ?
```
datasets-cli test ./datasets/mrqa --save_infos --all_configs --ignore_verifications
```
also cc @VictorSanh | [
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https://github.com/huggingface/datasets/pull/1117 | Fix incorrect MRQA train+SQuAD URL | > Thanks ! could you regenerate the dataset_infos.json file ?
>
> ```
> datasets-cli test ./datasets/mrqa --save_infos --all_configs --ignore_verifications
> ```
>
> also cc @VictorSanh
Updated the `dataset_infos.json` file. | Fix issue #1115
| 31 | text: Fix incorrect MRQA train+SQuAD URL
Fix issue #1115
> Thanks ! could you regenerate the dataset_infos.json file ?
>
> ```
> datasets-cli test ./datasets/mrqa --save_infos --all_configs --ignore_verifications
> ```
>
> also cc @VictorSanh
Updated the `dataset_infos.json` file. | [
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https://github.com/huggingface/datasets/pull/1116 | add dbpedia_14 dataset | Hi @hfawaz, this week we are doing the 🤗 `datasets` sprint (see some details [here](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176)).
Nothing more to do on your side but it means that if you register on the thread I linked above, you can have some goodies for the present dataset that you have already added (and a special goodie if you want to spend more time and add 2 other datasets as well).
If you want to join, just tell me (or post on the thread on the HuggingFace forum: https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176) | This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353. | 85 | text: add dbpedia_14 dataset
This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353.
Hi @hfawaz, this week we are doing the 🤗 `datasets` sprint (see some details [here](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176)).
Nothing more to do on your side but it means that if you register on the thread I linked above, you can have some goodies for the present dataset that you have already added (and a special goodie if you want to spend more time and add 2 other datasets as well).
If you want to join, just tell me (or post on the thread on the HuggingFace forum: https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176) | [
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https://github.com/huggingface/datasets/pull/1116 | add dbpedia_14 dataset | Hello @thomwolf
Thanks for the feedback and for this invitation, indeed I would be glad to join you guys (you can add me).
I will see if I have the time to implement a couple of datasets.
Cheers! | This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353. | 38 | text: add dbpedia_14 dataset
This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353.
Hello @thomwolf
Thanks for the feedback and for this invitation, indeed I would be glad to join you guys (you can add me).
I will see if I have the time to implement a couple of datasets.
Cheers! | [
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https://github.com/huggingface/datasets/pull/1116 | add dbpedia_14 dataset | @hfawaz invited you to the slack with your uha email.
Check your spam folder if you can't find the invitation :) | This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353. | 21 | text: add dbpedia_14 dataset
This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353.
@hfawaz invited you to the slack with your uha email.
Check your spam folder if you can't find the invitation :) | [
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https://github.com/huggingface/datasets/pull/1116 | add dbpedia_14 dataset | Oh thanks, but can you invite me on my gmail: hassanismailfawaz@gmail.com
UHA is my old organization, I haven't had the time to update my online profiles yet.
Thank you | This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353. | 29 | text: add dbpedia_14 dataset
This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353.
Oh thanks, but can you invite me on my gmail: hassanismailfawaz@gmail.com
UHA is my old organization, I haven't had the time to update my online profiles yet.
Thank you | [
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https://github.com/huggingface/datasets/pull/1105 | add xquad_r dataset | looks like this PR includes changes in many files than the ones for xquad_r, could you create a new branch and a new PR ? | 25 | text: add xquad_r dataset
looks like this PR includes changes in many files than the ones for xquad_r, could you create a new branch and a new PR ? | [
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|
https://github.com/huggingface/datasets/pull/1095 | Add TupleInf Open IE Dataset | Errors are in the CI are not related to this PR (RemoteDatasetError)
the CI is fixed on master so it's fine | For more information: https://allenai.org/data/tuple-ie | 21 | text: Add TupleInf Open IE Dataset
For more information: https://allenai.org/data/tuple-ie
Errors are in the CI are not related to this PR (RemoteDatasetError)
the CI is fixed on master so it's fine | [
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https://github.com/huggingface/datasets/pull/1095 | Add TupleInf Open IE Dataset | @lhoestq Added the dataset card. Please let me know if more information needs to be added. | For more information: https://allenai.org/data/tuple-ie | 16 | text: Add TupleInf Open IE Dataset
For more information: https://allenai.org/data/tuple-ie
@lhoestq Added the dataset card. Please let me know if more information needs to be added. | [
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https://github.com/huggingface/datasets/pull/1087 | Add Big Patent dataset | @lhoestq reduced the dummy data size to around 19MB in total and added the dataset card. | * More info on the dataset: https://evasharma.github.io/bigpatent/
* There's another raw version of the dataset available from tfds. However, they're quite large so I don't have the resources to fully test all the configs for that version yet. We'll try to add it later. | 16 | text: Add Big Patent dataset
* More info on the dataset: https://evasharma.github.io/bigpatent/
* There's another raw version of the dataset available from tfds. However, they're quite large so I don't have the resources to fully test all the configs for that version yet. We'll try to add it later.
@lhoestq reduced the dummy data size to around 19MB in total and added the dataset card. | [
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https://github.com/huggingface/datasets/pull/1087 | Add Big Patent dataset | @lhoestq so I ended up removing all the nested JSON objects in the gz datafile and keep only one object with minimal content: `{"publication_number": "US-8230922-B2", "abstract": "dummy abstract", "application_number": "US-201113163519-A", "description": "dummy description"}`.
They're reduced to 35KB in total (2.5KB per domain and 17.5KB for all domains), hopefully, they're small enough. | * More info on the dataset: https://evasharma.github.io/bigpatent/
* There's another raw version of the dataset available from tfds. However, they're quite large so I don't have the resources to fully test all the configs for that version yet. We'll try to add it later. | 51 | text: Add Big Patent dataset
* More info on the dataset: https://evasharma.github.io/bigpatent/
* There's another raw version of the dataset available from tfds. However, they're quite large so I don't have the resources to fully test all the configs for that version yet. We'll try to add it later.
@lhoestq so I ended up removing all the nested JSON objects in the gz datafile and keep only one object with minimal content: `{"publication_number": "US-8230922-B2", "abstract": "dummy abstract", "application_number": "US-201113163519-A", "description": "dummy description"}`.
They're reduced to 35KB in total (2.5KB per domain and 17.5KB for all domains), hopefully, they're small enough. | [
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https://github.com/huggingface/datasets/pull/1086 | adding cdt dataset | > Thanks for adding this one !
>
> I left a few comments
>
> after the change you'll need to regenerate the dataset_infos.json file as well
dataset_infos.json regenerated | - **Name:** *Cyberbullying Detection Task*
- **Description:** *The Cyberbullying Detection task was part of 2019 edition of PolEval competition. The goal is to predict if a given Twitter message contains a cyberbullying (harmful) content.*
- **Data:** *https://github.com/ptaszynski/cyberbullying-Polish*
- **Motivation:** *The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding.* | 30 | text: adding cdt dataset
- **Name:** *Cyberbullying Detection Task*
- **Description:** *The Cyberbullying Detection task was part of 2019 edition of PolEval competition. The goal is to predict if a given Twitter message contains a cyberbullying (harmful) content.*
- **Data:** *https://github.com/ptaszynski/cyberbullying-Polish*
- **Motivation:** *The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding.*
> Thanks for adding this one !
>
> I left a few comments
>
> after the change you'll need to regenerate the dataset_infos.json file as well
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https://github.com/huggingface/datasets/pull/1086 | adding cdt dataset | looks like this PR includes changes to many files other that the ones for CDT
could you create another branch and another PR please ? | - **Name:** *Cyberbullying Detection Task*
- **Description:** *The Cyberbullying Detection task was part of 2019 edition of PolEval competition. The goal is to predict if a given Twitter message contains a cyberbullying (harmful) content.*
- **Data:** *https://github.com/ptaszynski/cyberbullying-Polish*
- **Motivation:** *The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding.* | 25 | text: adding cdt dataset
- **Name:** *Cyberbullying Detection Task*
- **Description:** *The Cyberbullying Detection task was part of 2019 edition of PolEval competition. The goal is to predict if a given Twitter message contains a cyberbullying (harmful) content.*
- **Data:** *https://github.com/ptaszynski/cyberbullying-Polish*
- **Motivation:** *The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding.*
looks like this PR includes changes to many files other that the ones for CDT
could you create another branch and another PR please ? | [
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https://github.com/huggingface/datasets/pull/1068 | Add Pubmed (citation + abstract) dataset (2020). | It's not finished yet, I need to run the tests on the full dataset (it was running this weekend, there is an error somewhere deep)
| null | 25 | text: Add Pubmed (citation + abstract) dataset (2020).
It's not finished yet, I need to run the tests on the full dataset (it was running this weekend, there is an error somewhere deep)
| [
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https://github.com/huggingface/datasets/pull/1068 | Add Pubmed (citation + abstract) dataset (2020). | @yjernite Ready for review !
@thomwolf
So I tried to follow closely the original format that means I still had to drop information (namely tags on elements are simply discarded for now but they don't seem to carry critical information).
Some elements are also discarded they tend to not come up often:
- The most notable is Author affiliation, which seems to be all over the place in terms of what it look meaning it's hard to actually get a consistent format.
- Journal is the same, all the elements in there can be wildly different so I decided to drop it for now instead of trying to figure out a way to have a common presentation. (the DOI and medline ID are present so it can be recovered).
I think this PR could go as it but we probably should add a way to get easier information to use with a config.
For instance `{"title": "string", "abstract": "string", "authors": List[str], "substances": List[str]}` maybe ? (substances for instance is a tricky one, some substances only have an international identifier, some have simply a common name, some both)
It's relatively easy to do I think it's mostly discarding other fields and renaming some deep structure into a flat one. | null | 208 | text: Add Pubmed (citation + abstract) dataset (2020).
@yjernite Ready for review !
@thomwolf
So I tried to follow closely the original format that means I still had to drop information (namely tags on elements are simply discarded for now but they don't seem to carry critical information).
Some elements are also discarded they tend to not come up often:
- The most notable is Author affiliation, which seems to be all over the place in terms of what it look meaning it's hard to actually get a consistent format.
- Journal is the same, all the elements in there can be wildly different so I decided to drop it for now instead of trying to figure out a way to have a common presentation. (the DOI and medline ID are present so it can be recovered).
I think this PR could go as it but we probably should add a way to get easier information to use with a config.
For instance `{"title": "string", "abstract": "string", "authors": List[str], "substances": List[str]}` maybe ? (substances for instance is a tricky one, some substances only have an international identifier, some have simply a common name, some both)
It's relatively easy to do I think it's mostly discarding other fields and renaming some deep structure into a flat one. | [
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https://github.com/huggingface/datasets/pull/1066 | Add ChrEn | > I just saw your PR actually ^^
Somehow that still doesn't work, lmk if you have any ideas. | Adding the Cherokee English machine translation dataset of https://github.com/ZhangShiyue/ChrEn | 19 | text: Add ChrEn
Adding the Cherokee English machine translation dataset of https://github.com/ZhangShiyue/ChrEn
> I just saw your PR actually ^^
Somehow that still doesn't work, lmk if you have any ideas. | [
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https://github.com/huggingface/datasets/pull/1062 | Add KorNLU dataset | Nice thank you !
Can you regenerate the dataset_infos.json file ? Since we changed the features we must update it
Then I think we'll be good to merge :) | Added Korean NLU datasets. The link to the dataset can be found [here](https://github.com/kakaobrain/KorNLUDatasets) and the paper can be found [here](https://arxiv.org/abs/2004.03289)
**Note**: The MNLI tsv file is broken, so this code currently excludes the file. Please suggest other alternative if any @lhoestq
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | 29 | text: Add KorNLU dataset
Added Korean NLU datasets. The link to the dataset can be found [here](https://github.com/kakaobrain/KorNLUDatasets) and the paper can be found [here](https://arxiv.org/abs/2004.03289)
**Note**: The MNLI tsv file is broken, so this code currently excludes the file. Please suggest other alternative if any @lhoestq
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data
Nice thank you !
Can you regenerate the dataset_infos.json file ? Since we changed the features we must update it
Then I think we'll be good to merge :) | [
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https://github.com/huggingface/datasets/pull/1060 | Fix squad V2 metric script | The script with changes is used and tested in [#8924](https://github.com/huggingface/transformers/pull/8924). It gives the same results as the old `evaluate_squad` function when used on the same predictions. | The current squad v2 metric doesn't work with the squad (v1 or v2) datasets. The script is copied from `squad_evaluate` in transformers that requires the labels (with multiple answers) to be like this:
```
references = [{'id': 'a', 'answers': [
{'text': 'Denver Broncos', 'answer_start': 177},
{'text': 'Denver Broncos', 'answer_start': 177}
]}]
```
while the dataset had references like this:
```
references = [{'id': 'a', 'answers':
{'text': ['Denver Broncos' 'Denver Broncos'], 'answer_start': [177, 177]}
}]
```
Using one or the other format fails with the current squad v2 metric:
```
from datasets import load_metric
metric = load_metric("squad_v2")
predictions = [{'id': 'a', 'prediction_text': 'Denver Broncos', 'no_answer_probability': 0.0}]
references = [{'id': 'a', 'answers': [
{'text': 'Denver Broncos', 'answer_start': 177},
{'text': 'Denver Broncos', 'answer_start': 177}
]}]
metric.compute(predictions=predictions, references=references)
```
fails as well as
```
from datasets import load_metric
metric = load_metric("squad_v2")
predictions = [{'id': 'a', 'prediction_text': 'Denver Broncos', 'no_answer_probability': 0.0}]
references = [{'id': 'a', 'answers':
{'text': ['Denver Broncos' 'Denver Broncos'], 'answer_start': [177, 177]}
}]
metric.compute(predictions=predictions, references=references)
```
This is because arrow reformats the references behind the scene.
With this PR (tested locally), both the snippets up there work and return proper results. | 26 | text: Fix squad V2 metric script
The current squad v2 metric doesn't work with the squad (v1 or v2) datasets. The script is copied from `squad_evaluate` in transformers that requires the labels (with multiple answers) to be like this:
```
references = [{'id': 'a', 'answers': [
{'text': 'Denver Broncos', 'answer_start': 177},
{'text': 'Denver Broncos', 'answer_start': 177}
]}]
```
while the dataset had references like this:
```
references = [{'id': 'a', 'answers':
{'text': ['Denver Broncos' 'Denver Broncos'], 'answer_start': [177, 177]}
}]
```
Using one or the other format fails with the current squad v2 metric:
```
from datasets import load_metric
metric = load_metric("squad_v2")
predictions = [{'id': 'a', 'prediction_text': 'Denver Broncos', 'no_answer_probability': 0.0}]
references = [{'id': 'a', 'answers': [
{'text': 'Denver Broncos', 'answer_start': 177},
{'text': 'Denver Broncos', 'answer_start': 177}
]}]
metric.compute(predictions=predictions, references=references)
```
fails as well as
```
from datasets import load_metric
metric = load_metric("squad_v2")
predictions = [{'id': 'a', 'prediction_text': 'Denver Broncos', 'no_answer_probability': 0.0}]
references = [{'id': 'a', 'answers':
{'text': ['Denver Broncos' 'Denver Broncos'], 'answer_start': [177, 177]}
}]
metric.compute(predictions=predictions, references=references)
```
This is because arrow reformats the references behind the scene.
With this PR (tested locally), both the snippets up there work and return proper results.
The script with changes is used and tested in [#8924](https://github.com/huggingface/transformers/pull/8924). It gives the same results as the old `evaluate_squad` function when used on the same predictions. | [
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https://github.com/huggingface/datasets/pull/1059 | Add TLC | I have reduced the size of the dummy file and added README sections as you suggested. | Added TLC dataset | 16 | text: Add TLC
Added TLC dataset
I have reduced the size of the dummy file and added README sections as you suggested. | [
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https://github.com/huggingface/datasets/pull/1059 | Add TLC | I have a little issue to run the test. It seems there is no failed case in my machine. | Added TLC dataset | 19 | text: Add TLC
Added TLC dataset
I have a little issue to run the test. It seems there is no failed case in my machine. | [
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https://github.com/huggingface/datasets/pull/1059 | Add TLC | Thanks !
It looks like the PR includes changes to many other files than the ones of `tlc`, can you create another branch and another PR ? | Added TLC dataset | 27 | text: Add TLC
Added TLC dataset
Thanks !
It looks like the PR includes changes to many other files than the ones of `tlc`, can you create another branch and another PR ? | [
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https://github.com/huggingface/datasets/pull/1057 | Adding TamilMixSentiment | looks like this pr incldues changes about many other files than the ones for tamilMixSentiment, could you create another branch and another PR ? | 24 | text: Adding TamilMixSentiment
looks like this pr incldues changes about many other files than the ones for tamilMixSentiment, could you create another branch and another PR ? | [
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|
https://github.com/huggingface/datasets/pull/1055 | Add hebrew-sentiment | @elronbandel it looks like something went wrong with the renaming, as the old files are still in the PR. Can you `git rm datasets/hebrew-sentiment` ? | hebrew-sentiment dataset is ready! (including tests, tags etc) | 25 | text: Add hebrew-sentiment
hebrew-sentiment dataset is ready! (including tests, tags etc)
@elronbandel it looks like something went wrong with the renaming, as the old files are still in the PR. Can you `git rm datasets/hebrew-sentiment` ? | [
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https://github.com/huggingface/datasets/pull/1051 | Add Facebook SimpleQuestionV2 | I think @thomwolf may also be working on this one as part of the Babi benchmark in #945 | Add simple questions v2: https://research.fb.com/downloads/babi/ | 18 | text: Add Facebook SimpleQuestionV2
Add simple questions v2: https://research.fb.com/downloads/babi/
I think @thomwolf may also be working on this one as part of the Babi benchmark in #945 | [
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https://github.com/huggingface/datasets/pull/1050 | Add GoEmotions | Whoops, didn't mean for that to be merged yet (my bad). I'm reaching out to the authors since we'd like their feedback on the best way to have the `author` field anonymized or removed. Will send a patch once they get back to me. | Adds the GoEmotions dataset, a nice emotion classification dataset with 27 (multi-)label annotations on reddit comments. Includes both a large raw version and a narrowed version with predefined train/test/val splits, which I've included as separate configs with the latter as a default.
- Webpage/repo: https://github.com/google-research/google-research/tree/master/goemotions
- Paper: https://arxiv.org/abs/2005.00547 | 44 | text: Add GoEmotions
Adds the GoEmotions dataset, a nice emotion classification dataset with 27 (multi-)label annotations on reddit comments. Includes both a large raw version and a narrowed version with predefined train/test/val splits, which I've included as separate configs with the latter as a default.
- Webpage/repo: https://github.com/google-research/google-research/tree/master/goemotions
- Paper: https://arxiv.org/abs/2005.00547
Whoops, didn't mean for that to be merged yet (my bad). I'm reaching out to the authors since we'd like their feedback on the best way to have the `author` field anonymized or removed. Will send a patch once they get back to me. | [
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https://github.com/huggingface/datasets/pull/1047 | Add KorNLU | looks like this PR includes many changes to other files that the ones related to KorNLU
Could you create another branch and another PR please ? | Added Korean NLU datasets. The link to the dataset can be found [here](https://github.com/kakaobrain/KorNLUDatasets) and the paper can be found [here](https://arxiv.org/abs/2004.03289)
**Note**: The MNLI tsv file is broken, so this code currently excludes the file. Please suggest other alternative if any @lhoestq
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | 26 | text: Add KorNLU
Added Korean NLU datasets. The link to the dataset can be found [here](https://github.com/kakaobrain/KorNLUDatasets) and the paper can be found [here](https://arxiv.org/abs/2004.03289)
**Note**: The MNLI tsv file is broken, so this code currently excludes the file. Please suggest other alternative if any @lhoestq
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data
looks like this PR includes many changes to other files that the ones related to KorNLU
Could you create another branch and another PR please ? | [
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https://github.com/huggingface/datasets/pull/1045 | Add xitsonga ner corpus | Look like this PR includes changes to many other files than the ones related to xitsonga NER.
Could you create another branch and another PR please ? | 27 | text: Add xitsonga ner corpus
Look like this PR includes changes to many other files than the ones related to xitsonga NER.
Could you create another branch and another PR please ? | [
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|
https://github.com/huggingface/datasets/pull/1042 | Add Big Patent dataset | Looks like this PR include changes about many other files than the ones related to big patent.
Could you create another branch and another PR ? | - More info on the dataset: https://evasharma.github.io/bigpatent/
- There's another raw version of the dataset available from tfds. However, they're quite large so I don't have the resources to fully test all the configs for that version yet. We'll try to add it later.
- ~Currently, there are no dummy data for this dataset yet as I'm facing some problems with generating them. I'm trying to add them later.~ | 26 | text: Add Big Patent dataset
- More info on the dataset: https://evasharma.github.io/bigpatent/
- There's another raw version of the dataset available from tfds. However, they're quite large so I don't have the resources to fully test all the configs for that version yet. We'll try to add it later.
- ~Currently, there are no dummy data for this dataset yet as I'm facing some problems with generating them. I'm trying to add them later.~
Looks like this PR include changes about many other files than the ones related to big patent.
Could you create another branch and another PR ? | [
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https://github.com/huggingface/datasets/pull/1037 | Fix docs indentation issues | Yes @lhoestq, look at the docs site. For example, in https://huggingface.co/docs/datasets/add_dataset.html, look at the indentation in the code block under the sentence:
> Here are the features of the SQuAD dataset for instance, which is taken from the squad dataset loading script: | Replace tabs with spaces. | 42 | text: Fix docs indentation issues
Replace tabs with spaces.
Yes @lhoestq, look at the docs site. For example, in https://huggingface.co/docs/datasets/add_dataset.html, look at the indentation in the code block under the sentence:
> Here are the features of the SQuAD dataset for instance, which is taken from the squad dataset loading script: | [
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https://github.com/huggingface/datasets/pull/1036 | Add PerSenT | looks like this PR contains changes in many other files than the ones for PerSenT
can you create another branch and another PR ? | Added [Person's SentimenT](https://stonybrooknlp.github.io/PerSenT/) dataset. | 24 | text: Add PerSenT
Added [Person's SentimenT](https://stonybrooknlp.github.io/PerSenT/) dataset.
looks like this PR contains changes in many other files than the ones for PerSenT
can you create another branch and another PR ? | [
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https://github.com/huggingface/datasets/pull/1035 | add wiki_hop | Also the dummy data files are quite big (500KB)
If you could reduce that that would be nice (just look at the files inside and remove unecessary chunks of texts)
in general dummy data are just a few KB and we suggest to not get higher than 50KB
Having light dummy data makes the repo faster to clone | This PR adds the WikiHop dataset from the QAngaroo multi hop reading comprehension datasets
More info:
http://qangaroo.cs.ucl.ac.uk/index.html
| 58 | text: add wiki_hop
This PR adds the WikiHop dataset from the QAngaroo multi hop reading comprehension datasets
More info:
http://qangaroo.cs.ucl.ac.uk/index.html
Also the dummy data files are quite big (500KB)
If you could reduce that that would be nice (just look at the files inside and remove unecessary chunks of texts)
in general dummy data are just a few KB and we suggest to not get higher than 50KB
Having light dummy data makes the repo faster to clone | [
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https://github.com/huggingface/datasets/pull/1033 | Add support for ".txm" format | Hi ! yes sure :) can you just merge master into this branch before we merge ? | In dummy data generation, add support for XML-like ".txm" file format.
Also support filenames with additional compression extension: ".txm.gz". | 17 | text: Add support for ".txm" format
In dummy data generation, add support for XML-like ".txm" file format.
Also support filenames with additional compression extension: ".txm.gz".
Hi ! yes sure :) can you just merge master into this branch before we merge ? | [
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https://github.com/huggingface/datasets/pull/1032 | IIT B English to Hindi machine translation dataset | Please note that this dataset is actually behind a form that one needs to fill. However, the link is direct. I'm not sure what should the approach be in this case. | Adding IIT Bombay English-Hindi Corpus dataset
more info : http://www.cfilt.iitb.ac.in/iitb_parallel/ | 31 | text: IIT B English to Hindi machine translation dataset
Adding IIT Bombay English-Hindi Corpus dataset
more info : http://www.cfilt.iitb.ac.in/iitb_parallel/
Please note that this dataset is actually behind a form that one needs to fill. However, the link is direct. I'm not sure what should the approach be in this case. | [
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https://github.com/huggingface/datasets/pull/1032 | IIT B English to Hindi machine translation dataset | also pinging @thomwolf
The dataset webpage returns a form when trying to download the dataset (form here : http://www.cfilt.iitb.ac.in/iitb_parallel/dataset.html).
However the url we get with the form can be used for the dataset script.
Should we ask the authors or use the urls this way ? | Adding IIT Bombay English-Hindi Corpus dataset
more info : http://www.cfilt.iitb.ac.in/iitb_parallel/ | 46 | text: IIT B English to Hindi machine translation dataset
Adding IIT Bombay English-Hindi Corpus dataset
more info : http://www.cfilt.iitb.ac.in/iitb_parallel/
also pinging @thomwolf
The dataset webpage returns a form when trying to download the dataset (form here : http://www.cfilt.iitb.ac.in/iitb_parallel/dataset.html).
However the url we get with the form can be used for the dataset script.
Should we ask the authors or use the urls this way ? | [
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https://github.com/huggingface/datasets/pull/1032 | IIT B English to Hindi machine translation dataset | > also pinging @thomwolf
> The dataset webpage returns a form when trying to download the dataset (form here : http://www.cfilt.iitb.ac.in/iitb_parallel/dataset.html).
> However the url we get with the form can be used for the dataset script.
> Should we ask the authors or use the urls this way ?
I had discussion on this with @thomwolf . We have already sent email to author of this dataset. | Adding IIT Bombay English-Hindi Corpus dataset
more info : http://www.cfilt.iitb.ac.in/iitb_parallel/ | 68 | text: IIT B English to Hindi machine translation dataset
Adding IIT Bombay English-Hindi Corpus dataset
more info : http://www.cfilt.iitb.ac.in/iitb_parallel/
> also pinging @thomwolf
> The dataset webpage returns a form when trying to download the dataset (form here : http://www.cfilt.iitb.ac.in/iitb_parallel/dataset.html).
> However the url we get with the form can be used for the dataset script.
> Should we ask the authors or use the urls this way ?
I had discussion on this with @thomwolf . We have already sent email to author of this dataset. | [
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https://github.com/huggingface/datasets/pull/1029 | Add PEC | Hey @zhongpeixiang!
Really nice addition here!
Did you officially joined the sprint by posting [on the forum thread](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176) and joining our slack?
I can't seem to find you there! Should I add you directly with your gmail address? | A persona-based empathetic conversation dataset. | 38 | text: Add PEC
A persona-based empathetic conversation dataset.
Hey @zhongpeixiang!
Really nice addition here!
Did you officially joined the sprint by posting [on the forum thread](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176) and joining our slack?
I can't seem to find you there! Should I add you directly with your gmail address? | [
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https://github.com/huggingface/datasets/pull/1029 | Add PEC | > Hey @zhongpeixiang!
> Really nice addition here!
>
> Did you officially joined the sprint by posting [on the forum thread](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176) and joining our slack?
> I can't seem to find you there! Should I add you directly with your gmail address?
Thank you for the invitation. This initiative is awesome. Sadly I’m occupied by my thesis writing this month. Good luck 🤗 | A persona-based empathetic conversation dataset. | 64 | text: Add PEC
A persona-based empathetic conversation dataset.
> Hey @zhongpeixiang!
> Really nice addition here!
>
> Did you officially joined the sprint by posting [on the forum thread](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176) and joining our slack?
> I can't seem to find you there! Should I add you directly with your gmail address?
Thank you for the invitation. This initiative is awesome. Sadly I’m occupied by my thesis writing this month. Good luck 🤗 | [
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https://github.com/huggingface/datasets/pull/1029 | Add PEC | As you want @zhongpeixiang (I was maybe not clear but that just mean that by posting on the forum thread that you participated in the current event you will get a special gift (a tee-shirt) for the contribution that you have already done here :-) Nothing more to do) | A persona-based empathetic conversation dataset. | 49 | text: Add PEC
A persona-based empathetic conversation dataset.
As you want @zhongpeixiang (I was maybe not clear but that just mean that by posting on the forum thread that you participated in the current event you will get a special gift (a tee-shirt) for the contribution that you have already done here :-) Nothing more to do) | [
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https://github.com/huggingface/datasets/pull/1029 | Add PEC | > As you want @zhongpeixiang (I was maybe not clear but that just mean that by posting on the forum thread that you participated in the current event you will get a special gift (a tee-shirt) for the contribution that you have already done here :-) Nothing more to do)
Oh, I misunderstood the post. I'm glad to join. | A persona-based empathetic conversation dataset. | 59 | text: Add PEC
A persona-based empathetic conversation dataset.
> As you want @zhongpeixiang (I was maybe not clear but that just mean that by posting on the forum thread that you participated in the current event you will get a special gift (a tee-shirt) for the contribution that you have already done here :-) Nothing more to do)
Oh, I misunderstood the post. I'm glad to join. | [
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https://github.com/huggingface/datasets/pull/1025 | Add Sesotho Ner | looks like this PR include changes to other files (sepedi)
could you try to only include the files related to the addition of sesotho ner ? | 26 | text: Add Sesotho Ner
looks like this PR include changes to other files (sepedi)
could you try to only include the files related to the addition of sesotho ner ? | [
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|
https://github.com/huggingface/datasets/pull/1025 | Add Sesotho Ner | I think i need to clean up my local repo. I am committing everything a fresh after sepedi | 18 | text: Add Sesotho Ner
I think i need to clean up my local repo. I am committing everything a fresh after sepedi | [
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|
https://github.com/huggingface/datasets/pull/1025 | Add Sesotho Ner | Feel free to ping me when yuo have a clean PR and it's ready to review :) | 17 | text: Add Sesotho Ner
Feel free to ping me when yuo have a clean PR and it's ready to review :) | [
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|
https://github.com/huggingface/datasets/pull/1024 | Add ZEST: ZEroShot learning from Task descriptions | Looks good to me, we can ping the authors for more info later. And yes apply `other-task` labels liberally, we can sort them out later :)
Looks ready to merge when you're ready @joeddav | Adds the ZEST dataset on zero-shot learning from task descriptions from AI2.
- Webpage: https://allenai.org/data/zest
- Paper: https://arxiv.org/abs/2011.08115
The nature of this dataset made the supported task tags tricky if you wouldn't mind giving any feedback @yjernite. Also let me know if you think we should have a `other-task-generalization` or something like that... | 34 | text: Add ZEST: ZEroShot learning from Task descriptions
Adds the ZEST dataset on zero-shot learning from task descriptions from AI2.
- Webpage: https://allenai.org/data/zest
- Paper: https://arxiv.org/abs/2011.08115
The nature of this dataset made the supported task tags tricky if you wouldn't mind giving any feedback @yjernite. Also let me know if you think we should have a `other-task-generalization` or something like that...
Looks good to me, we can ping the authors for more info later. And yes apply `other-task` labels liberally, we can sort them out later :)
Looks ready to merge when you're ready @joeddav | [
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https://github.com/huggingface/datasets/pull/1021 | Add Gutenberg time references dataset | Description: "A clean data resource containing all explicit time references in a dataset of 52,183 novels whose full text is available via Project Gutenberg and the Hathi Trust Digital Library 2." > This is just the Gutenberg part.
Also, the paragraph at the top of the file would make a good Dataset Summary in the README :) | This PR adds the gutenberg_time dataset: https://arxiv.org/abs/2011.04124 | 57 | text: Add Gutenberg time references dataset
This PR adds the gutenberg_time dataset: https://arxiv.org/abs/2011.04124
Description: "A clean data resource containing all explicit time references in a dataset of 52,183 novels whose full text is available via Project Gutenberg and the Hathi Trust Digital Library 2." > This is just the Gutenberg part.
Also, the paragraph at the top of the file would make a good Dataset Summary in the README :) | [
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] |
https://github.com/huggingface/datasets/pull/1014 | Add SciTLDR Dataset (Take 2) | > If the CI fails just because of `RemoteDatasetTest` errors it's fine, they're fixed on master
The same 3 tests are failing again :(
```
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_norwegian_ner
``` | Adds the SciTLDR Dataset by AI2
Added the `README.md` card with tags to the best of my knowledge
Multi-target summaries or TLDRs of Scientific Documents
Continued from #986 | 32 | text: Add SciTLDR Dataset (Take 2)
Adds the SciTLDR Dataset by AI2
Added the `README.md` card with tags to the best of my knowledge
Multi-target summaries or TLDRs of Scientific Documents
Continued from #986
> If the CI fails just because of `RemoteDatasetTest` errors it's fine, they're fixed on master
The same 3 tests are failing again :(
```
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_norwegian_ner
``` | [
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https://github.com/huggingface/datasets/pull/1014 | Add SciTLDR Dataset (Take 2) | One trick if you want to add more datasets to avoid these errors : you can just rebase the master branch of your fork from the master branch of the repo. Then each time you make a new branch from master on your fork, it will include the fix for these errors | Adds the SciTLDR Dataset by AI2
Added the `README.md` card with tags to the best of my knowledge
Multi-target summaries or TLDRs of Scientific Documents
Continued from #986 | 52 | text: Add SciTLDR Dataset (Take 2)
Adds the SciTLDR Dataset by AI2
Added the `README.md` card with tags to the best of my knowledge
Multi-target summaries or TLDRs of Scientific Documents
Continued from #986
One trick if you want to add more datasets to avoid these errors : you can just rebase the master branch of your fork from the master branch of the repo. Then each time you make a new branch from master on your fork, it will include the fix for these errors | [
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https://github.com/huggingface/datasets/pull/1014 | Add SciTLDR Dataset (Take 2) | > One trick if you want to add more datasets to avoid these errors : you can just rebase the master branch of your fork from the master branch of the repo. Then each time you make a new branch from master on your fork, it will include the fix for these errors
Yes, I almost always do that, but somehow seems even this branch got old 😓
I also do the following if I directly create a new branch locally: `git checkout -b <branchname> upstream/master` so it stays up-to date irrespective of my fork, still don't know how this crept in again | Adds the SciTLDR Dataset by AI2
Added the `README.md` card with tags to the best of my knowledge
Multi-target summaries or TLDRs of Scientific Documents
Continued from #986 | 103 | text: Add SciTLDR Dataset (Take 2)
Adds the SciTLDR Dataset by AI2
Added the `README.md` card with tags to the best of my knowledge
Multi-target summaries or TLDRs of Scientific Documents
Continued from #986
> One trick if you want to add more datasets to avoid these errors : you can just rebase the master branch of your fork from the master branch of the repo. Then each time you make a new branch from master on your fork, it will include the fix for these errors
Yes, I almost always do that, but somehow seems even this branch got old 😓
I also do the following if I directly create a new branch locally: `git checkout -b <branchname> upstream/master` so it stays up-to date irrespective of my fork, still don't know how this crept in again | [
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https://github.com/huggingface/datasets/pull/1011 | Add Bilingual Corpus of Arabic-English Parallel Tweets | IMO, the problem with this dataset is that it is not really a text/nlp dataset. These are just collections of tweet ids. So, ultimately, one needs to crawl twitter to get the actual text. | Added Bilingual Corpus of Arabic-English Parallel Tweets. The link to the dataset can be found [here](https://alt.qcri.org/wp-content/uploads/2020/08/Bilingual-Corpus-of-Arabic-English-Parallel-Tweets.zip) and the paper can be found [here](https://www.aclweb.org/anthology/2020.bucc-1.3.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | 34 | text: Add Bilingual Corpus of Arabic-English Parallel Tweets
Added Bilingual Corpus of Arabic-English Parallel Tweets. The link to the dataset can be found [here](https://alt.qcri.org/wp-content/uploads/2020/08/Bilingual-Corpus-of-Arabic-English-Parallel-Tweets.zip) and the paper can be found [here](https://www.aclweb.org/anthology/2020.bucc-1.3.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data
IMO, the problem with this dataset is that it is not really a text/nlp dataset. These are just collections of tweet ids. So, ultimately, one needs to crawl twitter to get the actual text. | [
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https://github.com/huggingface/datasets/pull/1011 | Add Bilingual Corpus of Arabic-English Parallel Tweets | at least it's clear in the description that one needs to collect the tweets :
```
This resource is a result of a generic method for collecting parallel tweets.
``` | Added Bilingual Corpus of Arabic-English Parallel Tweets. The link to the dataset can be found [here](https://alt.qcri.org/wp-content/uploads/2020/08/Bilingual-Corpus-of-Arabic-English-Parallel-Tweets.zip) and the paper can be found [here](https://www.aclweb.org/anthology/2020.bucc-1.3.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | 30 | text: Add Bilingual Corpus of Arabic-English Parallel Tweets
Added Bilingual Corpus of Arabic-English Parallel Tweets. The link to the dataset can be found [here](https://alt.qcri.org/wp-content/uploads/2020/08/Bilingual-Corpus-of-Arabic-English-Parallel-Tweets.zip) and the paper can be found [here](https://www.aclweb.org/anthology/2020.bucc-1.3.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data
at least it's clear in the description that one needs to collect the tweets :
```
This resource is a result of a generic method for collecting parallel tweets.
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https://github.com/huggingface/datasets/pull/1011 | Add Bilingual Corpus of Arabic-English Parallel Tweets | Looks like this is failing for other datasets. Should I rebase it and push again?
Also rebasing and pushing is reflecting changes in many other files (ultimately forcing me to open a new branch and a new PR) any way to avoid this? | Added Bilingual Corpus of Arabic-English Parallel Tweets. The link to the dataset can be found [here](https://alt.qcri.org/wp-content/uploads/2020/08/Bilingual-Corpus-of-Arabic-English-Parallel-Tweets.zip) and the paper can be found [here](https://www.aclweb.org/anthology/2020.bucc-1.3.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | 43 | text: Add Bilingual Corpus of Arabic-English Parallel Tweets
Added Bilingual Corpus of Arabic-English Parallel Tweets. The link to the dataset can be found [here](https://alt.qcri.org/wp-content/uploads/2020/08/Bilingual-Corpus-of-Arabic-English-Parallel-Tweets.zip) and the paper can be found [here](https://www.aclweb.org/anthology/2020.bucc-1.3.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data
Looks like this is failing for other datasets. Should I rebase it and push again?
Also rebasing and pushing is reflecting changes in many other files (ultimately forcing me to open a new branch and a new PR) any way to avoid this? | [
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https://github.com/huggingface/datasets/pull/1002 | Adding Medal: MeDAL: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretraining | Could you fix the dummy data before we merge ?
Looks like the dummy `train.csv` is missing | null | 17 | text: Adding Medal: MeDAL: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretraining
Could you fix the dummy data before we merge ?
Looks like the dummy `train.csv` is missing | [
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https://github.com/huggingface/datasets/pull/997 | Microsoft CodeXGlue | #978 is working on adding code refinement
maybe we should keep the CodeXGlue benchmark (as glue) and don't merge the code_refinement dataset proposed in #978 ?
cc @reshinthadithyan | Datasets from https://github.com/microsoft/CodeXGLUE
This contains 13 datasets:
code_x_glue_cc_clone_detection_big_clone_bench
code_x_glue_cc_clone_detection_poj_104
code_x_glue_cc_cloze_testing_all
code_x_glue_cc_cloze_testing_maxmin
code_x_glue_cc_code_completion_line
code_x_glue_cc_code_completion_token
code_x_glue_cc_code_refinement
code_x_glue_cc_code_to_code_trans
code_x_glue_cc_defect_detection
code_x_glue_ct_code_to_text
code_x_glue_tc_nl_code_search_adv
code_x_glue_tc_text_to_code
code_x_glue_tt_text_to_text
| 28 | text: Microsoft CodeXGlue
Datasets from https://github.com/microsoft/CodeXGLUE
This contains 13 datasets:
code_x_glue_cc_clone_detection_big_clone_bench
code_x_glue_cc_clone_detection_poj_104
code_x_glue_cc_cloze_testing_all
code_x_glue_cc_cloze_testing_maxmin
code_x_glue_cc_code_completion_line
code_x_glue_cc_code_completion_token
code_x_glue_cc_code_refinement
code_x_glue_cc_code_to_code_trans
code_x_glue_cc_defect_detection
code_x_glue_ct_code_to_text
code_x_glue_tc_nl_code_search_adv
code_x_glue_tc_text_to_code
code_x_glue_tt_text_to_text
#978 is working on adding code refinement
maybe we should keep the CodeXGlue benchmark (as glue) and don't merge the code_refinement dataset proposed in #978 ?
cc @reshinthadithyan | [
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https://github.com/huggingface/datasets/pull/997 | Microsoft CodeXGlue | Hi @madlag and @lhoestq , I am extremely interested in getting this dataset into HF's library as I research in this area a lot. I see that it hasn't been updated in a while, but it is very close to being finished. If no one is currently working on this, I'd be happy to do any final touches that might be needed to get this merged. | Datasets from https://github.com/microsoft/CodeXGLUE
This contains 13 datasets:
code_x_glue_cc_clone_detection_big_clone_bench
code_x_glue_cc_clone_detection_poj_104
code_x_glue_cc_cloze_testing_all
code_x_glue_cc_cloze_testing_maxmin
code_x_glue_cc_code_completion_line
code_x_glue_cc_code_completion_token
code_x_glue_cc_code_refinement
code_x_glue_cc_code_to_code_trans
code_x_glue_cc_defect_detection
code_x_glue_ct_code_to_text
code_x_glue_tc_nl_code_search_adv
code_x_glue_tc_text_to_code
code_x_glue_tt_text_to_text
| 66 | text: Microsoft CodeXGlue
Datasets from https://github.com/microsoft/CodeXGLUE
This contains 13 datasets:
code_x_glue_cc_clone_detection_big_clone_bench
code_x_glue_cc_clone_detection_poj_104
code_x_glue_cc_cloze_testing_all
code_x_glue_cc_cloze_testing_maxmin
code_x_glue_cc_code_completion_line
code_x_glue_cc_code_completion_token
code_x_glue_cc_code_refinement
code_x_glue_cc_code_to_code_trans
code_x_glue_cc_defect_detection
code_x_glue_ct_code_to_text
code_x_glue_tc_nl_code_search_adv
code_x_glue_tc_text_to_code
code_x_glue_tt_text_to_text
Hi @madlag and @lhoestq , I am extremely interested in getting this dataset into HF's library as I research in this area a lot. I see that it hasn't been updated in a while, but it is very close to being finished. If no one is currently working on this, I'd be happy to do any final touches that might be needed to get this merged. | [
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https://github.com/huggingface/datasets/pull/997 | Microsoft CodeXGlue | Hi @ncoop57 ! Thanks for your interest and sorry for the inactivity on this PR.
Sure feel free to create another PR to continue this one ! This one was really close to being merged so I think it won't require that much changes. In addition to my previous comments, there should also be a "Contributions" subsection (see the template of the README [here](https://github.com/huggingface/datasets/blob/master/templates/README.md)) | Datasets from https://github.com/microsoft/CodeXGLUE
This contains 13 datasets:
code_x_glue_cc_clone_detection_big_clone_bench
code_x_glue_cc_clone_detection_poj_104
code_x_glue_cc_cloze_testing_all
code_x_glue_cc_cloze_testing_maxmin
code_x_glue_cc_code_completion_line
code_x_glue_cc_code_completion_token
code_x_glue_cc_code_refinement
code_x_glue_cc_code_to_code_trans
code_x_glue_cc_defect_detection
code_x_glue_ct_code_to_text
code_x_glue_tc_nl_code_search_adv
code_x_glue_tc_text_to_code
code_x_glue_tt_text_to_text
| 64 | text: Microsoft CodeXGlue
Datasets from https://github.com/microsoft/CodeXGLUE
This contains 13 datasets:
code_x_glue_cc_clone_detection_big_clone_bench
code_x_glue_cc_clone_detection_poj_104
code_x_glue_cc_cloze_testing_all
code_x_glue_cc_cloze_testing_maxmin
code_x_glue_cc_code_completion_line
code_x_glue_cc_code_completion_token
code_x_glue_cc_code_refinement
code_x_glue_cc_code_to_code_trans
code_x_glue_cc_defect_detection
code_x_glue_ct_code_to_text
code_x_glue_tc_nl_code_search_adv
code_x_glue_tc_text_to_code
code_x_glue_tt_text_to_text
Hi @ncoop57 ! Thanks for your interest and sorry for the inactivity on this PR.
Sure feel free to create another PR to continue this one ! This one was really close to being merged so I think it won't require that much changes. In addition to my previous comments, there should also be a "Contributions" subsection (see the template of the README [here](https://github.com/huggingface/datasets/blob/master/templates/README.md)) | [
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https://github.com/huggingface/datasets/pull/994 | Add Sepedi ner corpus | Looks like the PR includes commits about many other files.
Could you create a clean branch from master, and create another PR ? | 23 | text: Add Sepedi ner corpus
Looks like the PR includes commits about many other files.
Could you create a clean branch from master, and create another PR ? | [
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] |
|
https://github.com/huggingface/datasets/pull/986 | Add SciTLDR Dataset | CI failures seem to be unrelated (related to `norwegian_ner`)
```
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_norwegian_ner
``` | Adds the SciTLDR Dataset by AI2
Added README card with tags to the best of my knowledge
Multi-target summaries or TLDRs of Scientific Documents | 17 | text: Add SciTLDR Dataset
Adds the SciTLDR Dataset by AI2
Added README card with tags to the best of my knowledge
Multi-target summaries or TLDRs of Scientific Documents
CI failures seem to be unrelated (related to `norwegian_ner`)
```
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_norwegian_ner
``` | [
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https://github.com/huggingface/datasets/pull/986 | Add SciTLDR Dataset | Sorry, the rebase from master went horribly wrong, I guess I'll just open another PR
Closing this one due to a mistake in rebasing :( | Adds the SciTLDR Dataset by AI2
Added README card with tags to the best of my knowledge
Multi-target summaries or TLDRs of Scientific Documents | 25 | text: Add SciTLDR Dataset
Adds the SciTLDR Dataset by AI2
Added README card with tags to the best of my knowledge
Multi-target summaries or TLDRs of Scientific Documents
Sorry, the rebase from master went horribly wrong, I guess I'll just open another PR
Closing this one due to a mistake in rebasing :( | [
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https://github.com/huggingface/datasets/pull/985 | Add GAP dataset | This dataset already exists apparently, sorry :/
see
https://github.com/huggingface/datasets/blob/master/datasets/gap/gap.py
Feel free to re-use the dataset card you did for `/datasets/gap`
| GAP dataset
Gender bias coreference resolution | 20 | text: Add GAP dataset
GAP dataset
Gender bias coreference resolution
This dataset already exists apparently, sorry :/
see
https://github.com/huggingface/datasets/blob/master/datasets/gap/gap.py
Feel free to re-use the dataset card you did for `/datasets/gap`
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https://github.com/huggingface/datasets/pull/980 | Wongnai - Thai reviews dataset | Thank you for contributing a Thai dataset, @mapmeld ! I'm super hyped.
One comment I may add is that wongnai-corpus has two datasets: review classification (this) and word tokenization (https://github.com/wongnai/wongnai-corpus/blob/master/search/labeled_queries_by_judges.txt).
Would it be possible for you to rename this one something along the line of `wongnai-reviews` so that when/if we include the word tokenization dataset, we will know which is which.
This helps solve my check_code_quality issue.
```
make style
black --line-length 119 --target-version py36 datasets/wongnai
flake8 datasets/wongnai
isort datasets/wongnai/wongnai.py
``` | 40,000 reviews, previously released on GitHub ( https://github.com/wongnai/wongnai-corpus ) with an LGPL license, and on a closed Kaggle competition ( https://www.kaggle.com/c/wongnai-challenge-review-rating-prediction/ ) | 81 | text: Wongnai - Thai reviews dataset
40,000 reviews, previously released on GitHub ( https://github.com/wongnai/wongnai-corpus ) with an LGPL license, and on a closed Kaggle competition ( https://www.kaggle.com/c/wongnai-challenge-review-rating-prediction/ )
Thank you for contributing a Thai dataset, @mapmeld ! I'm super hyped.
One comment I may add is that wongnai-corpus has two datasets: review classification (this) and word tokenization (https://github.com/wongnai/wongnai-corpus/blob/master/search/labeled_queries_by_judges.txt).
Would it be possible for you to rename this one something along the line of `wongnai-reviews` so that when/if we include the word tokenization dataset, we will know which is which.
This helps solve my check_code_quality issue.
```
make style
black --line-length 119 --target-version py36 datasets/wongnai
flake8 datasets/wongnai
isort datasets/wongnai/wongnai.py
``` | [
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https://github.com/huggingface/datasets/pull/980 | Wongnai - Thai reviews dataset | @cstorm125 thanks! following your suggestions on formatting and on naming the dataset
I am writing a blog post about Thai NLP and transformers (example: mBERT does 1-2 character tokens instead of doing word segmentation), started adding this dataset to use as an example, and then saw you were adding other datasets. Great work! And if you know any Thai BERT models beyond https://github.com/ThAIKeras/bert we should maybe talk over email! | 40,000 reviews, previously released on GitHub ( https://github.com/wongnai/wongnai-corpus ) with an LGPL license, and on a closed Kaggle competition ( https://www.kaggle.com/c/wongnai-challenge-review-rating-prediction/ ) | 69 | text: Wongnai - Thai reviews dataset
40,000 reviews, previously released on GitHub ( https://github.com/wongnai/wongnai-corpus ) with an LGPL license, and on a closed Kaggle competition ( https://www.kaggle.com/c/wongnai-challenge-review-rating-prediction/ )
@cstorm125 thanks! following your suggestions on formatting and on naming the dataset
I am writing a blog post about Thai NLP and transformers (example: mBERT does 1-2 character tokens instead of doing word segmentation), started adding this dataset to use as an example, and then saw you were adding other datasets. Great work! And if you know any Thai BERT models beyond https://github.com/ThAIKeras/bert we should maybe talk over email! | [
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https://github.com/huggingface/datasets/pull/978 | Add code refinement | Yes, sorry I did not see earlier your message. I added 34 on the 35 datasets in CodeXGlue, tomorrow I will wrap it up, and so I will remove my version for code_refinement. Maybe we can just have a renaming after the merge, to have a consistent naming with all the other codexglue datasets ? What do you think @reshinthadithyan ? | ### OVERVIEW
Millions of open-source projects with numerous bug fixes
are available in code repositories. This proliferation
of software development histories can be leveraged to
learn how to fix common programming bugs
Code refinement aims to automatically fix bugs in the code,
which can contribute to reducing the cost of bug-fixes for developers.
Given a piece of Java code with bugs,
the task is to remove the bugs to output the refined code. | 61 | text: Add code refinement
### OVERVIEW
Millions of open-source projects with numerous bug fixes
are available in code repositories. This proliferation
of software development histories can be leveraged to
learn how to fix common programming bugs
Code refinement aims to automatically fix bugs in the code,
which can contribute to reducing the cost of bug-fixes for developers.
Given a piece of Java code with bugs,
the task is to remove the bugs to output the refined code.
Yes, sorry I did not see earlier your message. I added 34 on the 35 datasets in CodeXGlue, tomorrow I will wrap it up, and so I will remove my version for code_refinement. Maybe we can just have a renaming after the merge, to have a consistent naming with all the other codexglue datasets ? What do you think @reshinthadithyan ? | [
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https://github.com/huggingface/datasets/pull/978 | Add code refinement | > Yes, sorry I did not see earlier your message. I added 34 on the 35 datasets in CodeXGlue, tomorrow I will wrap it up, and so I will remove my version for code_refinement. Maybe we can just have a renaming after the merge, to have a consistent naming with all the other codexglue datasets ? What do you think @reshinthadithyan ?
Hello @madlag, I think you can retain that in your script. Let's stick onto the same file like how Glue is maintained. | ### OVERVIEW
Millions of open-source projects with numerous bug fixes
are available in code repositories. This proliferation
of software development histories can be leveraged to
learn how to fix common programming bugs
Code refinement aims to automatically fix bugs in the code,
which can contribute to reducing the cost of bug-fixes for developers.
Given a piece of Java code with bugs,
the task is to remove the bugs to output the refined code. | 84 | text: Add code refinement
### OVERVIEW
Millions of open-source projects with numerous bug fixes
are available in code repositories. This proliferation
of software development histories can be leveraged to
learn how to fix common programming bugs
Code refinement aims to automatically fix bugs in the code,
which can contribute to reducing the cost of bug-fixes for developers.
Given a piece of Java code with bugs,
the task is to remove the bugs to output the refined code.
> Yes, sorry I did not see earlier your message. I added 34 on the 35 datasets in CodeXGlue, tomorrow I will wrap it up, and so I will remove my version for code_refinement. Maybe we can just have a renaming after the merge, to have a consistent naming with all the other codexglue datasets ? What do you think @reshinthadithyan ?
Hello @madlag, I think you can retain that in your script. Let's stick onto the same file like how Glue is maintained. | [
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https://github.com/huggingface/datasets/pull/978 | Add code refinement | Hi @reshinthadithyan ! Are you still working on this version of the dataset or are we going with @madlag 's only ? | ### OVERVIEW
Millions of open-source projects with numerous bug fixes
are available in code repositories. This proliferation
of software development histories can be leveraged to
learn how to fix common programming bugs
Code refinement aims to automatically fix bugs in the code,
which can contribute to reducing the cost of bug-fixes for developers.
Given a piece of Java code with bugs,
the task is to remove the bugs to output the refined code. | 22 | text: Add code refinement
### OVERVIEW
Millions of open-source projects with numerous bug fixes
are available in code repositories. This proliferation
of software development histories can be leveraged to
learn how to fix common programming bugs
Code refinement aims to automatically fix bugs in the code,
which can contribute to reducing the cost of bug-fixes for developers.
Given a piece of Java code with bugs,
the task is to remove the bugs to output the refined code.
Hi @reshinthadithyan ! Are you still working on this version of the dataset or are we going with @madlag 's only ? | [
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https://github.com/huggingface/datasets/pull/978 | Add code refinement | > Hi @reshinthadithyan ! Are you still working on this version of the dataset or are we going with @madlag 's only ?
Hello, yes. We are going with Madlag's | ### OVERVIEW
Millions of open-source projects with numerous bug fixes
are available in code repositories. This proliferation
of software development histories can be leveraged to
learn how to fix common programming bugs
Code refinement aims to automatically fix bugs in the code,
which can contribute to reducing the cost of bug-fixes for developers.
Given a piece of Java code with bugs,
the task is to remove the bugs to output the refined code. | 30 | text: Add code refinement
### OVERVIEW
Millions of open-source projects with numerous bug fixes
are available in code repositories. This proliferation
of software development histories can be leveraged to
learn how to fix common programming bugs
Code refinement aims to automatically fix bugs in the code,
which can contribute to reducing the cost of bug-fixes for developers.
Given a piece of Java code with bugs,
the task is to remove the bugs to output the refined code.
> Hi @reshinthadithyan ! Are you still working on this version of the dataset or are we going with @madlag 's only ?
Hello, yes. We are going with Madlag's | [
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https://github.com/huggingface/datasets/pull/976 | Arabic pos dialect | looks like this PR includes changes about many other files than the oens for Araboc POS Dialect
Can you create a another branch and another PR please ? | A README.md and loading script for the Arabic POS Dialect dataset. The README is missing the sections on personal information, biases, and limitations, as it would probably be better for those to be filled by someone who can read the contents of the dataset and is familiar with Arabic NLP. | 28 | text: Arabic pos dialect
A README.md and loading script for the Arabic POS Dialect dataset. The README is missing the sections on personal information, biases, and limitations, as it would probably be better for those to be filled by someone who can read the contents of the dataset and is familiar with Arabic NLP.
looks like this PR includes changes about many other files than the oens for Araboc POS Dialect
Can you create a another branch and another PR please ? | [
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https://github.com/huggingface/datasets/pull/973 | Adding The Microsoft Terminology Collection dataset. | I have to manually copy a dataset_infos.json file from other dataset and modify it since the `datasets-cli` isn't able to handle manually downloaded datasets yet (as far as I know). | 30 | text: Adding The Microsoft Terminology Collection dataset.
I have to manually copy a dataset_infos.json file from other dataset and modify it since the `datasets-cli` isn't able to handle manually downloaded datasets yet (as far as I know). | [
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|
https://github.com/huggingface/datasets/pull/973 | Adding The Microsoft Terminology Collection dataset. | you can generate the dataset_infos.json file even for dataset with manual data
To do so just specify `--data_dir <path/to/the/folder/containing/the/manual/data>` | 19 | text: Adding The Microsoft Terminology Collection dataset.
you can generate the dataset_infos.json file even for dataset with manual data
To do so just specify `--data_dir <path/to/the/folder/containing/the/manual/data>` | [
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|
https://github.com/huggingface/datasets/pull/973 | Adding The Microsoft Terminology Collection dataset. | Also, dummy_data seems having difficulty to handle manually downloaded datasets. `python datasets-cli dummy_data datasets/ms_terms --data_dir ...` reported `error: unrecognized arguments: --data_dir` error. Without `--data_dir`, it reported this error:
```
Dataset ms_terms with config BuilderConfig(name='ms_terms-full', version=1.0.0, data_dir=None, data_files=None, description='...\n') seems to already open files in the method `_split_generators(...)`. You might consider to instead only open files in the method `_generate_examples(...)` instead. If this is not possible the dummy data has to be created with less guidance. Make sure you create the file None.
Traceback (most recent call last):
File "datasets-cli", line 36, in <module>
service.run()
File "/Users/lzhao/Downloads/huggingface/datasets/src/datasets/commands/dummy_data.py", line 326, in run
dataset_builder=dataset_builder, mock_dl_manager=mock_dl_manager
File "/Users/lzhao/Downloads/huggingface/datasets/src/datasets/commands/dummy_data.py", line 406, in _print_dummy_data_instructions
for split in generator_splits:
UnboundLocalError: local variable 'generator_splits' referenced before assignment
``` | 120 | text: Adding The Microsoft Terminology Collection dataset.
Also, dummy_data seems having difficulty to handle manually downloaded datasets. `python datasets-cli dummy_data datasets/ms_terms --data_dir ...` reported `error: unrecognized arguments: --data_dir` error. Without `--data_dir`, it reported this error:
```
Dataset ms_terms with config BuilderConfig(name='ms_terms-full', version=1.0.0, data_dir=None, data_files=None, description='...\n') seems to already open files in the method `_split_generators(...)`. You might consider to instead only open files in the method `_generate_examples(...)` instead. If this is not possible the dummy data has to be created with less guidance. Make sure you create the file None.
Traceback (most recent call last):
File "datasets-cli", line 36, in <module>
service.run()
File "/Users/lzhao/Downloads/huggingface/datasets/src/datasets/commands/dummy_data.py", line 326, in run
dataset_builder=dataset_builder, mock_dl_manager=mock_dl_manager
File "/Users/lzhao/Downloads/huggingface/datasets/src/datasets/commands/dummy_data.py", line 406, in _print_dummy_data_instructions
for split in generator_splits:
UnboundLocalError: local variable 'generator_splits' referenced before assignment
``` | [
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|
https://github.com/huggingface/datasets/pull/973 | Adding The Microsoft Terminology Collection dataset. | Oh yes `--data_dir` seems to only be supported for the `datasets_cli test` command. Sorry about that.
Can you try to build the dummy_data.zip file manually ?
It has to be inside `./datasets/ms_terms/dummy/ms_terms-full/1.0.0`.
Inside this folder, please create a folder `dummy_data` that contains a dummy file `MicrosoftTermCollection.tbx` (with just a few examples in it). Then you can zip the `dummy_data` folder to `dummy_data.zip`
Then you can check if it worked using the command
```
pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_ms_terms
```
Feel free to use some debugging print statements in your script if it doesn't work first try to see what `dl_manager.manual_dir` ends up being and also `path_to_manual_file`.
Feel free to ping me if you have other questions | 113 | text: Adding The Microsoft Terminology Collection dataset.
Oh yes `--data_dir` seems to only be supported for the `datasets_cli test` command. Sorry about that.
Can you try to build the dummy_data.zip file manually ?
It has to be inside `./datasets/ms_terms/dummy/ms_terms-full/1.0.0`.
Inside this folder, please create a folder `dummy_data` that contains a dummy file `MicrosoftTermCollection.tbx` (with just a few examples in it). Then you can zip the `dummy_data` folder to `dummy_data.zip`
Then you can check if it worked using the command
```
pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_ms_terms
```
Feel free to use some debugging print statements in your script if it doesn't work first try to see what `dl_manager.manual_dir` ends up being and also `path_to_manual_file`.
Feel free to ping me if you have other questions | [
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|
https://github.com/huggingface/datasets/pull/973 | Adding The Microsoft Terminology Collection dataset. | `pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_ms_terms` gave `1 passed, 4 warnings in 8.13s`. Existing datasets, like `wikihow`, and `newsroom`, also report 4 warnings. So, I guess that is not related to this dataset. | 29 | text: Adding The Microsoft Terminology Collection dataset.
`pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_ms_terms` gave `1 passed, 4 warnings in 8.13s`. Existing datasets, like `wikihow`, and `newsroom`, also report 4 warnings. So, I guess that is not related to this dataset. | [
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|
https://github.com/huggingface/datasets/pull/973 | Adding The Microsoft Terminology Collection dataset. | > Could you run `make style` before we merge @leoxzhao ?
Sure thing. Done. Thanks Quentin. I have other datasets in mind. All of which requires manual download. This process is very helpful | 33 | text: Adding The Microsoft Terminology Collection dataset.
> Could you run `make style` before we merge @leoxzhao ?
Sure thing. Done. Thanks Quentin. I have other datasets in mind. All of which requires manual download. This process is very helpful | [
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|
https://github.com/huggingface/datasets/pull/972 | Add Children's Book Test (CBT) dataset | Hi @lhoestq,
I guess this PR can be closed since we merged #2044?
I have used the same link for the homepage, as it is where the dataset is provided, hope that is okay? | Add the Children's Book Test (CBT) from Facebook (Hill et al. 2016).
Sentence completion given a few sentences as context from a children's book. | 34 | text: Add Children's Book Test (CBT) dataset
Add the Children's Book Test (CBT) from Facebook (Hill et al. 2016).
Sentence completion given a few sentences as context from a children's book.
Hi @lhoestq,
I guess this PR can be closed since we merged #2044?
I have used the same link for the homepage, as it is where the dataset is provided, hope that is okay? | [
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https://github.com/huggingface/datasets/pull/972 | Add Children's Book Test (CBT) dataset | Closing in favor of #2044, thanks again :)
> I have used the same link for the homepage, as it is where the dataset is provided, hope that is okay?
Yea it's ok actually, at that time I thought there was another homepage for this dataset | Add the Children's Book Test (CBT) from Facebook (Hill et al. 2016).
Sentence completion given a few sentences as context from a children's book. | 46 | text: Add Children's Book Test (CBT) dataset
Add the Children's Book Test (CBT) from Facebook (Hill et al. 2016).
Sentence completion given a few sentences as context from a children's book.
Closing in favor of #2044, thanks again :)
> I have used the same link for the homepage, as it is where the dataset is provided, hope that is okay?
Yea it's ok actually, at that time I thought there was another homepage for this dataset | [
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https://github.com/huggingface/datasets/pull/968 | ADD Afrikaans NER | One trick if you want to add other datasets: consider running these commands each time you want to add a new dataset
```
git checkout master
git fetch upstream
git rebase upstream/master
git checkout -b add-<my_dataset_name>
``` | Afrikaans NER corpus | 37 | text: ADD Afrikaans NER
Afrikaans NER corpus
One trick if you want to add other datasets: consider running these commands each time you want to add a new dataset
```
git checkout master
git fetch upstream
git rebase upstream/master
git checkout -b add-<my_dataset_name>
``` | [
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https://github.com/huggingface/datasets/pull/967 | Add CS Restaurants dataset | Oh yeah, for some reason I thought you had to do it after the merge, I'll get on it | This PR adds the Czech restaurants dataset for Czech NLG. | 19 | text: Add CS Restaurants dataset
This PR adds the Czech restaurants dataset for Czech NLG.
Oh yeah, for some reason I thought you had to do it after the merge, I'll get on it | [
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https://github.com/huggingface/datasets/pull/966 | Add CLINC150 Dataset | Looks like your PR now shows changes in many other files than the ones for CLINC150.
Feel free to create another branch and another PR | Added CLINC150 Dataset. The link to the dataset can be found [here](https://github.com/clinc/oos-eval) and the paper can be found [here](https://www.aclweb.org/anthology/D19-1131.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | 25 | text: Add CLINC150 Dataset
Added CLINC150 Dataset. The link to the dataset can be found [here](https://github.com/clinc/oos-eval) and the paper can be found [here](https://www.aclweb.org/anthology/D19-1131.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data
Looks like your PR now shows changes in many other files than the ones for CLINC150.
Feel free to create another branch and another PR | [
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https://github.com/huggingface/datasets/pull/964 | Adding the WebNLG dataset | This is task is part of the GEM suite so will actually need a more complete dataset card. I'm taking a break for now though and will get back to it before merging :) | This PR adds data from the WebNLG challenge, with one configuration per release and challenge iteration.
More information can be found [here](https://webnlg-challenge.loria.fr/)
Unfortunately, the data itself comes from a pretty large number of small XML files, so the dummy data ends up being quite large (8.4 MB even keeping only one example per file). | 34 | text: Adding the WebNLG dataset
This PR adds data from the WebNLG challenge, with one configuration per release and challenge iteration.
More information can be found [here](https://webnlg-challenge.loria.fr/)
Unfortunately, the data itself comes from a pretty large number of small XML files, so the dummy data ends up being quite large (8.4 MB even keeping only one example per file).
This is task is part of the GEM suite so will actually need a more complete dataset card. I'm taking a break for now though and will get back to it before merging :) | [
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https://github.com/huggingface/datasets/pull/958 | dataset(ncslgr): add initial loading script | @lhoestq I added the README files, and now the tests fail... (check commit history, only changed MD file)
The tests seem a bit unstable | clean #789 | 24 | text: dataset(ncslgr): add initial loading script
clean #789
@lhoestq I added the README files, and now the tests fail... (check commit history, only changed MD file)
The tests seem a bit unstable | [
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https://github.com/huggingface/datasets/pull/955 | Added PragmEval benchmark | > Really cool ! Thanks for adding this one :)
> Good job at adding all those citations for each task
>
> Looks like the dummy data test doesn't pass. Maybe some files are missing in the dummy_data.zip files ?
> The error reports `pragmeval/verifiability/train.tsv` to be missing
>
> Also could you add the tags part of the dataset card (the rest is optional) ?
> See more info here : https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md#tag-the-dataset-and-write-the-dataset-card
In the prior commits I generated dataset_infos and the dummy files myself
Now they are generated with the cli, and the tests now seem to be passing better
I will look into the tag
| 108 | text: Added PragmEval benchmark
> Really cool ! Thanks for adding this one :)
> Good job at adding all those citations for each task
>
> Looks like the dummy data test doesn't pass. Maybe some files are missing in the dummy_data.zip files ?
> The error reports `pragmeval/verifiability/train.tsv` to be missing
>
> Also could you add the tags part of the dataset card (the rest is optional) ?
> See more info here : https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md#tag-the-dataset-and-write-the-dataset-card
In the prior commits I generated dataset_infos and the dummy files myself
Now they are generated with the cli, and the tests now seem to be passing better
I will look into the tag
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|
https://github.com/huggingface/datasets/pull/955 | Added PragmEval benchmark | Looks like you did a good job with dummy data in the first place !
The downside of automatically generated dummy data is that the files are heavier (here 40KB per file).
If you could replace the generated dummy files with the one you created yourself it would be awesome, since the one you did yourself are way lighter (around 1KB per file). Using small files make `git clone` run faster so we encourage to use small dummy_data files. | 79 | text: Added PragmEval benchmark
Looks like you did a good job with dummy data in the first place !
The downside of automatically generated dummy data is that the files are heavier (here 40KB per file).
If you could replace the generated dummy files with the one you created yourself it would be awesome, since the one you did yourself are way lighter (around 1KB per file). Using small files make `git clone` run faster so we encourage to use small dummy_data files. | [
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|
https://github.com/huggingface/datasets/pull/955 | Added PragmEval benchmark | > could you rebase from master ? it should fix the CI
I think it is due to the file structure of the dummy data that causes test failure. The automatically generated dummy data pass the tests | 37 | text: Added PragmEval benchmark
> could you rebase from master ? it should fix the CI
I think it is due to the file structure of the dummy data that causes test failure. The automatically generated dummy data pass the tests | [
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|
https://github.com/huggingface/datasets/pull/955 | Added PragmEval benchmark | Indeed the error reports that `pragmeval/verifiability/train.tsv` is missing for the verifiability dummy_data.zip file.
To fix that you should add the missing data files in each dummy_data.zip file.
To test that your dummy data work you can run
```
RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_
```
if some file is missing it should tell you which one | 53 | text: Added PragmEval benchmark
Indeed the error reports that `pragmeval/verifiability/train.tsv` is missing for the verifiability dummy_data.zip file.
To fix that you should add the missing data files in each dummy_data.zip file.
To test that your dummy data work you can run
```
RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_
```
if some file is missing it should tell you which one | [
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|
https://github.com/huggingface/datasets/pull/955 | Added PragmEval benchmark | Also it looks like you haven't rebased from master yet, even though you did a `rebase` commit.
rebasing should fix the other CI fails | 24 | text: Added PragmEval benchmark
Also it looks like you haven't rebased from master yet, even though you did a `rebase` commit.
rebasing should fix the other CI fails | [
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|
https://github.com/huggingface/datasets/pull/955 | Added PragmEval benchmark | Hey @sileod! Super nice to see you participating ;)
Did you officially joined the sprint by posting on [the forum thread](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176) and joining our slack?
I can't seem to find you there! Should I add you directly with your gmail address? | 41 | text: Added PragmEval benchmark
Hey @sileod! Super nice to see you participating ;)
Did you officially joined the sprint by posting on [the forum thread](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176) and joining our slack?
I can't seem to find you there! Should I add you directly with your gmail address? | [
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|
https://github.com/huggingface/datasets/pull/954 | add prachathai67k | Test failing for same issues as https://github.com/huggingface/datasets/pull/939
Please advise.
```
=========================== short test summary info ============================
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_xglue
===== 7 failed, 1309 passed, 932 skipped, 11 warnings in 166.71s (0:02:46) =====
``` | `prachathai-67k`: News Article Corpus and Multi-label Text Classificdation from Prachathai.com
The prachathai-67k dataset was scraped from the news site Prachathai.
We filtered out those articles with less than 500 characters of body text, mostly images and cartoons.
It contains 67,889 articles wtih 12 curated tags from August 24, 2004 to November 15, 2018.
The dataset was originally scraped by @lukkiddd and cleaned by @cstorm125.
You can also see preliminary exploration at https://github.com/PyThaiNLP/prachathai-67k/blob/master/exploration.ipynb | 44 | text: add prachathai67k
`prachathai-67k`: News Article Corpus and Multi-label Text Classificdation from Prachathai.com
The prachathai-67k dataset was scraped from the news site Prachathai.
We filtered out those articles with less than 500 characters of body text, mostly images and cartoons.
It contains 67,889 articles wtih 12 curated tags from August 24, 2004 to November 15, 2018.
The dataset was originally scraped by @lukkiddd and cleaned by @cstorm125.
You can also see preliminary exploration at https://github.com/PyThaiNLP/prachathai-67k/blob/master/exploration.ipynb
Test failing for same issues as https://github.com/huggingface/datasets/pull/939
Please advise.
```
=========================== short test summary info ============================
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_xglue
===== 7 failed, 1309 passed, 932 skipped, 11 warnings in 166.71s (0:02:46) =====
``` | [
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https://github.com/huggingface/datasets/pull/953 | added health_fact dataset | Hi @lhoestq,
Initially I tried int(-1) only in place of nan labels and missing values but I kept on getting this error ```pyarrow.lib.ArrowTypeError: Expected bytes, got a 'int' object``` maybe because I'm sending int values (-1) to objects which are string type | Added dataset Explainable Fact-Checking for Public Health Claims (dataset_id: health_fact) | 42 | text: added health_fact dataset
Added dataset Explainable Fact-Checking for Public Health Claims (dataset_id: health_fact)
Hi @lhoestq,
Initially I tried int(-1) only in place of nan labels and missing values but I kept on getting this error ```pyarrow.lib.ArrowTypeError: Expected bytes, got a 'int' object``` maybe because I'm sending int values (-1) to objects which are string type | [
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] |
https://github.com/huggingface/datasets/pull/941 | Add People's Daily NER dataset | > LGTM thanks :)
>
>
>
> Before we merge, could you add a dataset card ? see here for more info: https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md#tag-the-dataset-and-write-the-dataset-card
>
>
>
> Note that only the tags at the top of the dataset card are mandatory, if you feel like it's going to take too much time writing the rest to fill it all you can just skip the paragraphs
Nope. I don't think there is a citation. Also, can I do the dataset card later (maybe in bulk)? | 85 | text: Add People's Daily NER dataset
> LGTM thanks :)
>
>
>
> Before we merge, could you add a dataset card ? see here for more info: https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md#tag-the-dataset-and-write-the-dataset-card
>
>
>
> Note that only the tags at the top of the dataset card are mandatory, if you feel like it's going to take too much time writing the rest to fill it all you can just skip the paragraphs
Nope. I don't think there is a citation. Also, can I do the dataset card later (maybe in bulk)? | [
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|
https://github.com/huggingface/datasets/pull/941 | Add People's Daily NER dataset | We're doing one PR = one dataset to keep track of things. Feel free to add the tags later in this PR if you want to.
Also only the tags are required now, because we don't want people spending too much time on the cards | 45 | text: Add People's Daily NER dataset
We're doing one PR = one dataset to keep track of things. Feel free to add the tags later in this PR if you want to.
Also only the tags are required now, because we don't want people spending too much time on the cards | [
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|
https://github.com/huggingface/datasets/pull/939 | add wisesight_sentiment | @lhoestq Thanks, Quentin. Removed the .ipynb_checkpoints and edited the README.md. The tests are failing because of other dataets. I'm figuring out why since the commits only have changes on `wisesight_sentiment`
```
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_xglue
``` | Add `wisesight_sentiment` Social media messages in Thai language with sentiment label (positive, neutral, negative, question)
Model Card:
---
YAML tags:
annotations_creators:
- expert-generated
language_creators:
- found
languages:
- th
licenses:
- cc0-1.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
# Dataset Card for wisesight_sentiment
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Homepage:** https://github.com/PyThaiNLP/wisesight-sentiment
- **Repository:** https://github.com/PyThaiNLP/wisesight-sentiment
- **Paper:**
- **Leaderboard:** https://www.kaggle.com/c/wisesight-sentiment/
- **Point of Contact:** https://github.com/PyThaiNLP/
### Dataset Summary
Wisesight Sentiment Corpus: Social media messages in Thai language with sentiment label (positive, neutral, negative, question)
- Released to public domain under Creative Commons Zero v1.0 Universal license.
- Labels: {"pos": 0, "neu": 1, "neg": 2, "q": 3}
- Size: 26,737 messages
- Language: Central Thai
- Style: Informal and conversational. With some news headlines and advertisement.
- Time period: Around 2016 to early 2019. With small amount from other period.
- Domains: Mixed. Majority are consumer products and services (restaurants, cosmetics, drinks, car, hotels), with some current affairs.
- Privacy:
- Only messages that made available to the public on the internet (websites, blogs, social network sites).
- For Facebook, this means the public comments (everyone can see) that made on a public page.
- Private/protected messages and messages in groups, chat, and inbox are not included.
- Alternations and modifications:
- Keep in mind that this corpus does not statistically represent anything in the language register.
- Large amount of messages are not in their original form. Personal data are removed or masked.
- Duplicated, leading, and trailing whitespaces are removed. Other punctuations, symbols, and emojis are kept intact.
(Mis)spellings are kept intact.
- Messages longer than 2,000 characters are removed.
- Long non-Thai messages are removed. Duplicated message (exact match) are removed.
- More characteristics of the data can be explore [this notebook](https://github.com/PyThaiNLP/wisesight-sentiment/blob/master/exploration.ipynb)
### Supported Tasks and Leaderboards
Sentiment analysis / [Kaggle Leaderboard](https://www.kaggle.com/c/wisesight-sentiment/)
### Languages
Thai
## Dataset Structure
### Data Instances
```
{'category': 'pos', 'texts': 'น่าสนนน'}
{'category': 'neu', 'texts': 'ครับ #phithanbkk'}
{'category': 'neg', 'texts': 'ซื้อแต่ผ้าอนามัยแบบเย็นมาค่ะ แบบว่าอีห่ากูนอนไม่ได้'}
{'category': 'q', 'texts': 'มีแอลกอฮอลมั้ยคะ'}
```
### Data Fields
- `texts`: texts
- `category`: sentiment of texts ranging from `pos` (positive; 0), `neu` (neutral; 1), `neg` (negative; 2) and `q` (question; 3)
### Data Splits
| | train | valid | test |
|-----------|-------|-------|-------|
| # samples | 21628 | 2404 | 2671 |
| # neu | 11795 | 1291 | 1453 |
| # neg | 5491 | 637 | 683 |
| # pos | 3866 | 434 | 478 |
| # q | 476 | 42 | 57 |
| avg words | 27.21 | 27.18 | 27.12 |
| avg chars | 89.82 | 89.50 | 90.36 |
## Dataset Creation
### Curation Rationale
Originally, the dataset was conceived for the [In-class Kaggle Competition](https://www.kaggle.com/c/wisesight-sentiment/) at Chulalongkorn university by [Ekapol Chuangsuwanich](https://www.cp.eng.chula.ac.th/en/about/faculty/ekapolc/) (Faculty of Engineering, Chulalongkorn University). It has since become one of the benchmarks for sentiment analysis in Thai.
### Source Data
#### Initial Data Collection and Normalization
- Style: Informal and conversational. With some news headlines and advertisement.
- Time period: Around 2016 to early 2019. With small amount from other period.
- Domains: Mixed. Majority are consumer products and services (restaurants, cosmetics, drinks, car, hotels), with some current affairs.
- Privacy:
- Only messages that made available to the public on the internet (websites, blogs, social network sites).
- For Facebook, this means the public comments (everyone can see) that made on a public page.
- Private/protected messages and messages in groups, chat, and inbox are not included.
- Usernames and non-public figure names are removed
- Phone numbers are masked (e.g. 088-888-8888, 09-9999-9999, 0-2222-2222)
- If you see any personal data still remain in the set, please tell us - so we can remove them.
- Alternations and modifications:
- Keep in mind that this corpus does not statistically represent anything in the language register.
- Large amount of messages are not in their original form. Personal data are removed or masked.
- Duplicated, leading, and trailing whitespaces are removed. Other punctuations, symbols, and emojis are kept intact.
- (Mis)spellings are kept intact.
- Messages longer than 2,000 characters are removed.
- Long non-Thai messages are removed. Duplicated message (exact match) are removed.
#### Who are the source language producers?
Social media users in Thailand
### Annotations
#### Annotation process
- Sentiment values are assigned by human annotators.
- A human annotator put his/her best effort to assign just one label, out of four, to a message.
- Agreement, enjoyment, and satisfaction are positive. Disagreement, sadness, and disappointment are negative.
- Showing interest in a topic or in a product is counted as positive. In this sense, a question about a particular product could has a positive sentiment value, if it shows the interest in the product.
- Saying that other product or service is better is counted as negative.
- General information or news title tend to be counted as neutral.
#### Who are the annotators?
Outsourced annotators hired by [Wisesight (Thailand) Co., Ltd.](https://github.com/wisesight/)
### Personal and Sensitive Information
- We trying to exclude any known personally identifiable information from this data set.
- Usernames and non-public figure names are removed
- Phone numbers are masked (e.g. 088-888-8888, 09-9999-9999, 0-2222-2222)
- If you see any personal data still remain in the set, please tell us - so we can remove them.
## Considerations for Using the Data
### Social Impact of Dataset
- `wisesight_sentiment` is the first and one of the few open datasets for sentiment analysis of social media data in Thai
- There are risks of personal information that escape the anonymization process
### Discussion of Biases
- A message can be ambiguous. When possible, the judgement will be based solely on the text itself.
- In some situation, like when the context is missing, the annotator may have to rely on his/her own world knowledge and just guess.
- In some cases, the human annotator may have an access to the message's context, like an image. These additional information are not included as part of this corpus.
### Other Known Limitations
- The labels are imbalanced; over half of the texts are `neu` (neutral) whereas there are very few `q` (question).
- Misspellings in social media texts make word tokenization process for Thai difficult, thus impacting the model performance
## Additional Information
### Dataset Curators
Thanks [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp) community, [Kitsuchart Pasupa](http://www.it.kmitl.ac.th/~kitsuchart/) (Faculty of Information Technology, King Mongkut's Institute of Technology Ladkrabang), and [Ekapol Chuangsuwanich](https://www.cp.eng.chula.ac.th/en/about/faculty/ekapolc/) (Faculty of Engineering, Chulalongkorn University) for advice. The original Kaggle competition, using the first version of this corpus, can be found at https://www.kaggle.com/c/wisesight-sentiment/
### Licensing Information
- If applicable, copyright of each message content belongs to the original poster.
- **Annotation data (labels) are released to public domain.**
- [Wisesight (Thailand) Co., Ltd.](https://github.com/wisesight/) helps facilitate the annotation, but does not necessarily agree upon the labels made by the human annotators. This annotation is for research purpose and does not reflect the professional work that Wisesight has been done for its customers.
- The human annotator does not necessarily agree or disagree with the message. Likewise, the label he/she made to the message does not necessarily reflect his/her personal view towards the message.
### Citation Information
Please cite the following if you make use of the dataset:
Arthit Suriyawongkul, Ekapol Chuangsuwanich, Pattarawat Chormai, and Charin Polpanumas. 2019. **PyThaiNLP/wisesight-sentiment: First release.** September.
BibTeX:
```
@software{bact_2019_3457447,
author = {Suriyawongkul, Arthit and
Chuangsuwanich, Ekapol and
Chormai, Pattarawat and
Polpanumas, Charin},
title = {PyThaiNLP/wisesight-sentiment: First release},
month = sep,
year = 2019,
publisher = {Zenodo},
version = {v1.0},
doi = {10.5281/zenodo.3457447},
url = {https://doi.org/10.5281/zenodo.3457447}
}
```
| 46 | text: add wisesight_sentiment
Add `wisesight_sentiment` Social media messages in Thai language with sentiment label (positive, neutral, negative, question)
Model Card:
---
YAML tags:
annotations_creators:
- expert-generated
language_creators:
- found
languages:
- th
licenses:
- cc0-1.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
# Dataset Card for wisesight_sentiment
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Homepage:** https://github.com/PyThaiNLP/wisesight-sentiment
- **Repository:** https://github.com/PyThaiNLP/wisesight-sentiment
- **Paper:**
- **Leaderboard:** https://www.kaggle.com/c/wisesight-sentiment/
- **Point of Contact:** https://github.com/PyThaiNLP/
### Dataset Summary
Wisesight Sentiment Corpus: Social media messages in Thai language with sentiment label (positive, neutral, negative, question)
- Released to public domain under Creative Commons Zero v1.0 Universal license.
- Labels: {"pos": 0, "neu": 1, "neg": 2, "q": 3}
- Size: 26,737 messages
- Language: Central Thai
- Style: Informal and conversational. With some news headlines and advertisement.
- Time period: Around 2016 to early 2019. With small amount from other period.
- Domains: Mixed. Majority are consumer products and services (restaurants, cosmetics, drinks, car, hotels), with some current affairs.
- Privacy:
- Only messages that made available to the public on the internet (websites, blogs, social network sites).
- For Facebook, this means the public comments (everyone can see) that made on a public page.
- Private/protected messages and messages in groups, chat, and inbox are not included.
- Alternations and modifications:
- Keep in mind that this corpus does not statistically represent anything in the language register.
- Large amount of messages are not in their original form. Personal data are removed or masked.
- Duplicated, leading, and trailing whitespaces are removed. Other punctuations, symbols, and emojis are kept intact.
(Mis)spellings are kept intact.
- Messages longer than 2,000 characters are removed.
- Long non-Thai messages are removed. Duplicated message (exact match) are removed.
- More characteristics of the data can be explore [this notebook](https://github.com/PyThaiNLP/wisesight-sentiment/blob/master/exploration.ipynb)
### Supported Tasks and Leaderboards
Sentiment analysis / [Kaggle Leaderboard](https://www.kaggle.com/c/wisesight-sentiment/)
### Languages
Thai
## Dataset Structure
### Data Instances
```
{'category': 'pos', 'texts': 'น่าสนนน'}
{'category': 'neu', 'texts': 'ครับ #phithanbkk'}
{'category': 'neg', 'texts': 'ซื้อแต่ผ้าอนามัยแบบเย็นมาค่ะ แบบว่าอีห่ากูนอนไม่ได้'}
{'category': 'q', 'texts': 'มีแอลกอฮอลมั้ยคะ'}
```
### Data Fields
- `texts`: texts
- `category`: sentiment of texts ranging from `pos` (positive; 0), `neu` (neutral; 1), `neg` (negative; 2) and `q` (question; 3)
### Data Splits
| | train | valid | test |
|-----------|-------|-------|-------|
| # samples | 21628 | 2404 | 2671 |
| # neu | 11795 | 1291 | 1453 |
| # neg | 5491 | 637 | 683 |
| # pos | 3866 | 434 | 478 |
| # q | 476 | 42 | 57 |
| avg words | 27.21 | 27.18 | 27.12 |
| avg chars | 89.82 | 89.50 | 90.36 |
## Dataset Creation
### Curation Rationale
Originally, the dataset was conceived for the [In-class Kaggle Competition](https://www.kaggle.com/c/wisesight-sentiment/) at Chulalongkorn university by [Ekapol Chuangsuwanich](https://www.cp.eng.chula.ac.th/en/about/faculty/ekapolc/) (Faculty of Engineering, Chulalongkorn University). It has since become one of the benchmarks for sentiment analysis in Thai.
### Source Data
#### Initial Data Collection and Normalization
- Style: Informal and conversational. With some news headlines and advertisement.
- Time period: Around 2016 to early 2019. With small amount from other period.
- Domains: Mixed. Majority are consumer products and services (restaurants, cosmetics, drinks, car, hotels), with some current affairs.
- Privacy:
- Only messages that made available to the public on the internet (websites, blogs, social network sites).
- For Facebook, this means the public comments (everyone can see) that made on a public page.
- Private/protected messages and messages in groups, chat, and inbox are not included.
- Usernames and non-public figure names are removed
- Phone numbers are masked (e.g. 088-888-8888, 09-9999-9999, 0-2222-2222)
- If you see any personal data still remain in the set, please tell us - so we can remove them.
- Alternations and modifications:
- Keep in mind that this corpus does not statistically represent anything in the language register.
- Large amount of messages are not in their original form. Personal data are removed or masked.
- Duplicated, leading, and trailing whitespaces are removed. Other punctuations, symbols, and emojis are kept intact.
- (Mis)spellings are kept intact.
- Messages longer than 2,000 characters are removed.
- Long non-Thai messages are removed. Duplicated message (exact match) are removed.
#### Who are the source language producers?
Social media users in Thailand
### Annotations
#### Annotation process
- Sentiment values are assigned by human annotators.
- A human annotator put his/her best effort to assign just one label, out of four, to a message.
- Agreement, enjoyment, and satisfaction are positive. Disagreement, sadness, and disappointment are negative.
- Showing interest in a topic or in a product is counted as positive. In this sense, a question about a particular product could has a positive sentiment value, if it shows the interest in the product.
- Saying that other product or service is better is counted as negative.
- General information or news title tend to be counted as neutral.
#### Who are the annotators?
Outsourced annotators hired by [Wisesight (Thailand) Co., Ltd.](https://github.com/wisesight/)
### Personal and Sensitive Information
- We trying to exclude any known personally identifiable information from this data set.
- Usernames and non-public figure names are removed
- Phone numbers are masked (e.g. 088-888-8888, 09-9999-9999, 0-2222-2222)
- If you see any personal data still remain in the set, please tell us - so we can remove them.
## Considerations for Using the Data
### Social Impact of Dataset
- `wisesight_sentiment` is the first and one of the few open datasets for sentiment analysis of social media data in Thai
- There are risks of personal information that escape the anonymization process
### Discussion of Biases
- A message can be ambiguous. When possible, the judgement will be based solely on the text itself.
- In some situation, like when the context is missing, the annotator may have to rely on his/her own world knowledge and just guess.
- In some cases, the human annotator may have an access to the message's context, like an image. These additional information are not included as part of this corpus.
### Other Known Limitations
- The labels are imbalanced; over half of the texts are `neu` (neutral) whereas there are very few `q` (question).
- Misspellings in social media texts make word tokenization process for Thai difficult, thus impacting the model performance
## Additional Information
### Dataset Curators
Thanks [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp) community, [Kitsuchart Pasupa](http://www.it.kmitl.ac.th/~kitsuchart/) (Faculty of Information Technology, King Mongkut's Institute of Technology Ladkrabang), and [Ekapol Chuangsuwanich](https://www.cp.eng.chula.ac.th/en/about/faculty/ekapolc/) (Faculty of Engineering, Chulalongkorn University) for advice. The original Kaggle competition, using the first version of this corpus, can be found at https://www.kaggle.com/c/wisesight-sentiment/
### Licensing Information
- If applicable, copyright of each message content belongs to the original poster.
- **Annotation data (labels) are released to public domain.**
- [Wisesight (Thailand) Co., Ltd.](https://github.com/wisesight/) helps facilitate the annotation, but does not necessarily agree upon the labels made by the human annotators. This annotation is for research purpose and does not reflect the professional work that Wisesight has been done for its customers.
- The human annotator does not necessarily agree or disagree with the message. Likewise, the label he/she made to the message does not necessarily reflect his/her personal view towards the message.
### Citation Information
Please cite the following if you make use of the dataset:
Arthit Suriyawongkul, Ekapol Chuangsuwanich, Pattarawat Chormai, and Charin Polpanumas. 2019. **PyThaiNLP/wisesight-sentiment: First release.** September.
BibTeX:
```
@software{bact_2019_3457447,
author = {Suriyawongkul, Arthit and
Chuangsuwanich, Ekapol and
Chormai, Pattarawat and
Polpanumas, Charin},
title = {PyThaiNLP/wisesight-sentiment: First release},
month = sep,
year = 2019,
publisher = {Zenodo},
version = {v1.0},
doi = {10.5281/zenodo.3457447},
url = {https://doi.org/10.5281/zenodo.3457447}
}
```
@lhoestq Thanks, Quentin. Removed the .ipynb_checkpoints and edited the README.md. The tests are failing because of other dataets. I'm figuring out why since the commits only have changes on `wisesight_sentiment`
```
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_flue
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_norwegian_ner
FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_xglue
``` | [
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https://github.com/huggingface/datasets/pull/939 | add wisesight_sentiment | @cstorm125 I really like the dataset and dataset card but there seems to have been a rebase issue at some point since it's now changing 140 files :D
Could you rebase from master? | Add `wisesight_sentiment` Social media messages in Thai language with sentiment label (positive, neutral, negative, question)
Model Card:
---
YAML tags:
annotations_creators:
- expert-generated
language_creators:
- found
languages:
- th
licenses:
- cc0-1.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
# Dataset Card for wisesight_sentiment
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Homepage:** https://github.com/PyThaiNLP/wisesight-sentiment
- **Repository:** https://github.com/PyThaiNLP/wisesight-sentiment
- **Paper:**
- **Leaderboard:** https://www.kaggle.com/c/wisesight-sentiment/
- **Point of Contact:** https://github.com/PyThaiNLP/
### Dataset Summary
Wisesight Sentiment Corpus: Social media messages in Thai language with sentiment label (positive, neutral, negative, question)
- Released to public domain under Creative Commons Zero v1.0 Universal license.
- Labels: {"pos": 0, "neu": 1, "neg": 2, "q": 3}
- Size: 26,737 messages
- Language: Central Thai
- Style: Informal and conversational. With some news headlines and advertisement.
- Time period: Around 2016 to early 2019. With small amount from other period.
- Domains: Mixed. Majority are consumer products and services (restaurants, cosmetics, drinks, car, hotels), with some current affairs.
- Privacy:
- Only messages that made available to the public on the internet (websites, blogs, social network sites).
- For Facebook, this means the public comments (everyone can see) that made on a public page.
- Private/protected messages and messages in groups, chat, and inbox are not included.
- Alternations and modifications:
- Keep in mind that this corpus does not statistically represent anything in the language register.
- Large amount of messages are not in their original form. Personal data are removed or masked.
- Duplicated, leading, and trailing whitespaces are removed. Other punctuations, symbols, and emojis are kept intact.
(Mis)spellings are kept intact.
- Messages longer than 2,000 characters are removed.
- Long non-Thai messages are removed. Duplicated message (exact match) are removed.
- More characteristics of the data can be explore [this notebook](https://github.com/PyThaiNLP/wisesight-sentiment/blob/master/exploration.ipynb)
### Supported Tasks and Leaderboards
Sentiment analysis / [Kaggle Leaderboard](https://www.kaggle.com/c/wisesight-sentiment/)
### Languages
Thai
## Dataset Structure
### Data Instances
```
{'category': 'pos', 'texts': 'น่าสนนน'}
{'category': 'neu', 'texts': 'ครับ #phithanbkk'}
{'category': 'neg', 'texts': 'ซื้อแต่ผ้าอนามัยแบบเย็นมาค่ะ แบบว่าอีห่ากูนอนไม่ได้'}
{'category': 'q', 'texts': 'มีแอลกอฮอลมั้ยคะ'}
```
### Data Fields
- `texts`: texts
- `category`: sentiment of texts ranging from `pos` (positive; 0), `neu` (neutral; 1), `neg` (negative; 2) and `q` (question; 3)
### Data Splits
| | train | valid | test |
|-----------|-------|-------|-------|
| # samples | 21628 | 2404 | 2671 |
| # neu | 11795 | 1291 | 1453 |
| # neg | 5491 | 637 | 683 |
| # pos | 3866 | 434 | 478 |
| # q | 476 | 42 | 57 |
| avg words | 27.21 | 27.18 | 27.12 |
| avg chars | 89.82 | 89.50 | 90.36 |
## Dataset Creation
### Curation Rationale
Originally, the dataset was conceived for the [In-class Kaggle Competition](https://www.kaggle.com/c/wisesight-sentiment/) at Chulalongkorn university by [Ekapol Chuangsuwanich](https://www.cp.eng.chula.ac.th/en/about/faculty/ekapolc/) (Faculty of Engineering, Chulalongkorn University). It has since become one of the benchmarks for sentiment analysis in Thai.
### Source Data
#### Initial Data Collection and Normalization
- Style: Informal and conversational. With some news headlines and advertisement.
- Time period: Around 2016 to early 2019. With small amount from other period.
- Domains: Mixed. Majority are consumer products and services (restaurants, cosmetics, drinks, car, hotels), with some current affairs.
- Privacy:
- Only messages that made available to the public on the internet (websites, blogs, social network sites).
- For Facebook, this means the public comments (everyone can see) that made on a public page.
- Private/protected messages and messages in groups, chat, and inbox are not included.
- Usernames and non-public figure names are removed
- Phone numbers are masked (e.g. 088-888-8888, 09-9999-9999, 0-2222-2222)
- If you see any personal data still remain in the set, please tell us - so we can remove them.
- Alternations and modifications:
- Keep in mind that this corpus does not statistically represent anything in the language register.
- Large amount of messages are not in their original form. Personal data are removed or masked.
- Duplicated, leading, and trailing whitespaces are removed. Other punctuations, symbols, and emojis are kept intact.
- (Mis)spellings are kept intact.
- Messages longer than 2,000 characters are removed.
- Long non-Thai messages are removed. Duplicated message (exact match) are removed.
#### Who are the source language producers?
Social media users in Thailand
### Annotations
#### Annotation process
- Sentiment values are assigned by human annotators.
- A human annotator put his/her best effort to assign just one label, out of four, to a message.
- Agreement, enjoyment, and satisfaction are positive. Disagreement, sadness, and disappointment are negative.
- Showing interest in a topic or in a product is counted as positive. In this sense, a question about a particular product could has a positive sentiment value, if it shows the interest in the product.
- Saying that other product or service is better is counted as negative.
- General information or news title tend to be counted as neutral.
#### Who are the annotators?
Outsourced annotators hired by [Wisesight (Thailand) Co., Ltd.](https://github.com/wisesight/)
### Personal and Sensitive Information
- We trying to exclude any known personally identifiable information from this data set.
- Usernames and non-public figure names are removed
- Phone numbers are masked (e.g. 088-888-8888, 09-9999-9999, 0-2222-2222)
- If you see any personal data still remain in the set, please tell us - so we can remove them.
## Considerations for Using the Data
### Social Impact of Dataset
- `wisesight_sentiment` is the first and one of the few open datasets for sentiment analysis of social media data in Thai
- There are risks of personal information that escape the anonymization process
### Discussion of Biases
- A message can be ambiguous. When possible, the judgement will be based solely on the text itself.
- In some situation, like when the context is missing, the annotator may have to rely on his/her own world knowledge and just guess.
- In some cases, the human annotator may have an access to the message's context, like an image. These additional information are not included as part of this corpus.
### Other Known Limitations
- The labels are imbalanced; over half of the texts are `neu` (neutral) whereas there are very few `q` (question).
- Misspellings in social media texts make word tokenization process for Thai difficult, thus impacting the model performance
## Additional Information
### Dataset Curators
Thanks [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp) community, [Kitsuchart Pasupa](http://www.it.kmitl.ac.th/~kitsuchart/) (Faculty of Information Technology, King Mongkut's Institute of Technology Ladkrabang), and [Ekapol Chuangsuwanich](https://www.cp.eng.chula.ac.th/en/about/faculty/ekapolc/) (Faculty of Engineering, Chulalongkorn University) for advice. The original Kaggle competition, using the first version of this corpus, can be found at https://www.kaggle.com/c/wisesight-sentiment/
### Licensing Information
- If applicable, copyright of each message content belongs to the original poster.
- **Annotation data (labels) are released to public domain.**
- [Wisesight (Thailand) Co., Ltd.](https://github.com/wisesight/) helps facilitate the annotation, but does not necessarily agree upon the labels made by the human annotators. This annotation is for research purpose and does not reflect the professional work that Wisesight has been done for its customers.
- The human annotator does not necessarily agree or disagree with the message. Likewise, the label he/she made to the message does not necessarily reflect his/her personal view towards the message.
### Citation Information
Please cite the following if you make use of the dataset:
Arthit Suriyawongkul, Ekapol Chuangsuwanich, Pattarawat Chormai, and Charin Polpanumas. 2019. **PyThaiNLP/wisesight-sentiment: First release.** September.
BibTeX:
```
@software{bact_2019_3457447,
author = {Suriyawongkul, Arthit and
Chuangsuwanich, Ekapol and
Chormai, Pattarawat and
Polpanumas, Charin},
title = {PyThaiNLP/wisesight-sentiment: First release},
month = sep,
year = 2019,
publisher = {Zenodo},
version = {v1.0},
doi = {10.5281/zenodo.3457447},
url = {https://doi.org/10.5281/zenodo.3457447}
}
```
| 33 | text: add wisesight_sentiment
Add `wisesight_sentiment` Social media messages in Thai language with sentiment label (positive, neutral, negative, question)
Model Card:
---
YAML tags:
annotations_creators:
- expert-generated
language_creators:
- found
languages:
- th
licenses:
- cc0-1.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
# Dataset Card for wisesight_sentiment
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Homepage:** https://github.com/PyThaiNLP/wisesight-sentiment
- **Repository:** https://github.com/PyThaiNLP/wisesight-sentiment
- **Paper:**
- **Leaderboard:** https://www.kaggle.com/c/wisesight-sentiment/
- **Point of Contact:** https://github.com/PyThaiNLP/
### Dataset Summary
Wisesight Sentiment Corpus: Social media messages in Thai language with sentiment label (positive, neutral, negative, question)
- Released to public domain under Creative Commons Zero v1.0 Universal license.
- Labels: {"pos": 0, "neu": 1, "neg": 2, "q": 3}
- Size: 26,737 messages
- Language: Central Thai
- Style: Informal and conversational. With some news headlines and advertisement.
- Time period: Around 2016 to early 2019. With small amount from other period.
- Domains: Mixed. Majority are consumer products and services (restaurants, cosmetics, drinks, car, hotels), with some current affairs.
- Privacy:
- Only messages that made available to the public on the internet (websites, blogs, social network sites).
- For Facebook, this means the public comments (everyone can see) that made on a public page.
- Private/protected messages and messages in groups, chat, and inbox are not included.
- Alternations and modifications:
- Keep in mind that this corpus does not statistically represent anything in the language register.
- Large amount of messages are not in their original form. Personal data are removed or masked.
- Duplicated, leading, and trailing whitespaces are removed. Other punctuations, symbols, and emojis are kept intact.
(Mis)spellings are kept intact.
- Messages longer than 2,000 characters are removed.
- Long non-Thai messages are removed. Duplicated message (exact match) are removed.
- More characteristics of the data can be explore [this notebook](https://github.com/PyThaiNLP/wisesight-sentiment/blob/master/exploration.ipynb)
### Supported Tasks and Leaderboards
Sentiment analysis / [Kaggle Leaderboard](https://www.kaggle.com/c/wisesight-sentiment/)
### Languages
Thai
## Dataset Structure
### Data Instances
```
{'category': 'pos', 'texts': 'น่าสนนน'}
{'category': 'neu', 'texts': 'ครับ #phithanbkk'}
{'category': 'neg', 'texts': 'ซื้อแต่ผ้าอนามัยแบบเย็นมาค่ะ แบบว่าอีห่ากูนอนไม่ได้'}
{'category': 'q', 'texts': 'มีแอลกอฮอลมั้ยคะ'}
```
### Data Fields
- `texts`: texts
- `category`: sentiment of texts ranging from `pos` (positive; 0), `neu` (neutral; 1), `neg` (negative; 2) and `q` (question; 3)
### Data Splits
| | train | valid | test |
|-----------|-------|-------|-------|
| # samples | 21628 | 2404 | 2671 |
| # neu | 11795 | 1291 | 1453 |
| # neg | 5491 | 637 | 683 |
| # pos | 3866 | 434 | 478 |
| # q | 476 | 42 | 57 |
| avg words | 27.21 | 27.18 | 27.12 |
| avg chars | 89.82 | 89.50 | 90.36 |
## Dataset Creation
### Curation Rationale
Originally, the dataset was conceived for the [In-class Kaggle Competition](https://www.kaggle.com/c/wisesight-sentiment/) at Chulalongkorn university by [Ekapol Chuangsuwanich](https://www.cp.eng.chula.ac.th/en/about/faculty/ekapolc/) (Faculty of Engineering, Chulalongkorn University). It has since become one of the benchmarks for sentiment analysis in Thai.
### Source Data
#### Initial Data Collection and Normalization
- Style: Informal and conversational. With some news headlines and advertisement.
- Time period: Around 2016 to early 2019. With small amount from other period.
- Domains: Mixed. Majority are consumer products and services (restaurants, cosmetics, drinks, car, hotels), with some current affairs.
- Privacy:
- Only messages that made available to the public on the internet (websites, blogs, social network sites).
- For Facebook, this means the public comments (everyone can see) that made on a public page.
- Private/protected messages and messages in groups, chat, and inbox are not included.
- Usernames and non-public figure names are removed
- Phone numbers are masked (e.g. 088-888-8888, 09-9999-9999, 0-2222-2222)
- If you see any personal data still remain in the set, please tell us - so we can remove them.
- Alternations and modifications:
- Keep in mind that this corpus does not statistically represent anything in the language register.
- Large amount of messages are not in their original form. Personal data are removed or masked.
- Duplicated, leading, and trailing whitespaces are removed. Other punctuations, symbols, and emojis are kept intact.
- (Mis)spellings are kept intact.
- Messages longer than 2,000 characters are removed.
- Long non-Thai messages are removed. Duplicated message (exact match) are removed.
#### Who are the source language producers?
Social media users in Thailand
### Annotations
#### Annotation process
- Sentiment values are assigned by human annotators.
- A human annotator put his/her best effort to assign just one label, out of four, to a message.
- Agreement, enjoyment, and satisfaction are positive. Disagreement, sadness, and disappointment are negative.
- Showing interest in a topic or in a product is counted as positive. In this sense, a question about a particular product could has a positive sentiment value, if it shows the interest in the product.
- Saying that other product or service is better is counted as negative.
- General information or news title tend to be counted as neutral.
#### Who are the annotators?
Outsourced annotators hired by [Wisesight (Thailand) Co., Ltd.](https://github.com/wisesight/)
### Personal and Sensitive Information
- We trying to exclude any known personally identifiable information from this data set.
- Usernames and non-public figure names are removed
- Phone numbers are masked (e.g. 088-888-8888, 09-9999-9999, 0-2222-2222)
- If you see any personal data still remain in the set, please tell us - so we can remove them.
## Considerations for Using the Data
### Social Impact of Dataset
- `wisesight_sentiment` is the first and one of the few open datasets for sentiment analysis of social media data in Thai
- There are risks of personal information that escape the anonymization process
### Discussion of Biases
- A message can be ambiguous. When possible, the judgement will be based solely on the text itself.
- In some situation, like when the context is missing, the annotator may have to rely on his/her own world knowledge and just guess.
- In some cases, the human annotator may have an access to the message's context, like an image. These additional information are not included as part of this corpus.
### Other Known Limitations
- The labels are imbalanced; over half of the texts are `neu` (neutral) whereas there are very few `q` (question).
- Misspellings in social media texts make word tokenization process for Thai difficult, thus impacting the model performance
## Additional Information
### Dataset Curators
Thanks [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp) community, [Kitsuchart Pasupa](http://www.it.kmitl.ac.th/~kitsuchart/) (Faculty of Information Technology, King Mongkut's Institute of Technology Ladkrabang), and [Ekapol Chuangsuwanich](https://www.cp.eng.chula.ac.th/en/about/faculty/ekapolc/) (Faculty of Engineering, Chulalongkorn University) for advice. The original Kaggle competition, using the first version of this corpus, can be found at https://www.kaggle.com/c/wisesight-sentiment/
### Licensing Information
- If applicable, copyright of each message content belongs to the original poster.
- **Annotation data (labels) are released to public domain.**
- [Wisesight (Thailand) Co., Ltd.](https://github.com/wisesight/) helps facilitate the annotation, but does not necessarily agree upon the labels made by the human annotators. This annotation is for research purpose and does not reflect the professional work that Wisesight has been done for its customers.
- The human annotator does not necessarily agree or disagree with the message. Likewise, the label he/she made to the message does not necessarily reflect his/her personal view towards the message.
### Citation Information
Please cite the following if you make use of the dataset:
Arthit Suriyawongkul, Ekapol Chuangsuwanich, Pattarawat Chormai, and Charin Polpanumas. 2019. **PyThaiNLP/wisesight-sentiment: First release.** September.
BibTeX:
```
@software{bact_2019_3457447,
author = {Suriyawongkul, Arthit and
Chuangsuwanich, Ekapol and
Chormai, Pattarawat and
Polpanumas, Charin},
title = {PyThaiNLP/wisesight-sentiment: First release},
month = sep,
year = 2019,
publisher = {Zenodo},
version = {v1.0},
doi = {10.5281/zenodo.3457447},
url = {https://doi.org/10.5281/zenodo.3457447}
}
```
@cstorm125 I really like the dataset and dataset card but there seems to have been a rebase issue at some point since it's now changing 140 files :D
Could you rebase from master? | [
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https://github.com/huggingface/datasets/pull/935 | add PIB dataset | Hi,
I am unable to get success in these tests. Can someone help me by pointing out possible errors?
Thanks | This pull request will add PIB dataset. | 20 | text: add PIB dataset
This pull request will add PIB dataset.
Hi,
I am unable to get success in these tests. Can someone help me by pointing out possible errors?
Thanks | [
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