update readme

README.md

@@ -69,30 +69,15 @@ configs:
     path: intensity/test-*
 ---
 # Dataset Card for NoReC TSA
+This is a dataset for Targeted Sentiment Analysis (TSA) in Norwegian, derived from the the fine-grained annotations of N[NoReC_fine](https://github.com/ltgoslo/norec_fine). The dataset contains tokenized Norwegian sentences where each token is tagged for sentiment expressed within the sentence towards that token. 
 
+Since a sentiment target may be the target of several sentiment expressions, these are resolved to a final sentiment polarity (and intensity) using the conversion script in [NoReC_tsa](https://github.com/ltgoslo/norec_tsa). There is no "mixed" sentiment category. When a target is the receiver of both positive and negative sentiment, the strongest wins. If a tie, the last sentiment wins. 
 
-## Dataset Description
-
-<!--- **Homepage:**  --->
-- **Repository:** 
-https://github.com/ltgoslo/norec_tsa
-- **Paper:** 
-[A Fine-Grained Sentiment Dataset for Norwegian](https://aclanthology.org/2020.lrec-1.618/)
-
-<!---
-- **Leaderboard:** 
-- **Point of Contact:** 
---->
-
-### Dataset Summary
-The dataset contains tokenized Norwegian sentences where each token is tagged for sentiment expressed towards that token. The dataset is derived from the manually annotated [NoReC_fine](https://github.com/ltgoslo/norec_fine) with rich annotations for each sentiment expression in the texts.  
-The texts are a subset of the Norewegian Review Corpus  [NoReC](https://github.com/ltgoslo/norec).
-
-### Supported Tasks and Leaderboards
-[NorBench](https://github.com/ltgoslo/norbench) provides TSA evaluation scripts using this dataset, and a leaderboard comparing large language models for downstream NLP tasks in Norwegian.  
-
-### Languages
-Norwegian: Predominantly Bokmål written variant.
+- **Curated by:** The [SANT](https://www.mn.uio.no/ifi/english/research/projects/sant/) project (Sentiment Analysis for Norwegian Text) at the [Language Technology Group](https://www.mn.uio.no/ifi/english/research/groups/ltg/) (LTG) at the University of Oslo
+- **Funded by:** The [SANT](https://www.mn.uio.no/ifi/english/research/projects/sant/) is funded by the [Research Council of Norway](https://www.forskningsradet.no/en/) (NFR grant number 270908).
+- **Shared by:** The [SANT](https://www.mn.uio.no/ifi/english/research/projects/sant/) project (Sentiment Analysis for Norwegian Text) at the [Language Technology Group](https://www.mn.uio.no/ifi/english/research/groups/ltg/) (LTG) at the University of Oslo
+- **License:** The data is distributed under a [Creative Commons Attribution-NonCommercial licence](https://creativecommons.org/licenses/by-nc/4.0/) (CC BY-NC 4.0). The licence is motivated by the need to block the possibility of third parties redistributing the orignal reviews for commercial purposes. Note that machine learned models, extracted lexicons, embeddings, and similar resources that are created on the basis of NoReC are not considered to contain the original data and so can be freely used also for commercial purposes despite the non-commercial condition.
+- **Language:** Norwegian ("no"): Predominantly Bokmål (nb) written variant.
 
 | variant   | split   |   sents |   docs |
 |:-----|:--------|--------:|-------:|
@@ -101,8 +86,14 @@ Norwegian: Predominantly Bokmål written variant.
 | nb   | train   |    8556 |    323 |
 | nn   | train   |      78 |      4 |
 
-## Fine-tuned models
-[`ltg/norbert3-large_TSA`](https://huggingface.co/ltg/norbert3-large_TSA)
+## Dataset Sources
+
+- **Repository:** https://github.com/ltgoslo/norec_tsa
+- **Paper:** The underlying NoReC_fine dataset is described in the paper [A Fine-Grained Sentiment Dataset for Norwegian](https://aclanthology.org/2020.lrec-1.618/) by Øvrelid et al., published at LREC 2020.
+
+## Uses
+The data is intended to be used for training and testing models for TSA token classification; identifying and classifying sentiment targets in Norwegian sentences.  
+Example models fine-tuned on this dataset can be found at [huggingface.co/collections/ltg/sentiment-analysis](https://huggingface.co/collections/ltg/sentiment-analysis-65c49c7247a0ffffa9897155)
 
 ## Dataset Structure
 The dataset comes in two flavours:
@@ -127,16 +118,12 @@ Config "intensity"  example instance:
  'tsa_tags': ['O', 'O', 'B-targ-Positive-2', 'O']}
 ```
 
-
-
 ### Data Fields
 - idx(str): Unique document-and sentence identifier from [NoReC_fine](https://github.com/ltgoslo/norec_fine). The 6-digit document identifier can also be used to look up the text and its metadata in [NoReC](https://github.com/ltgoslo/norec).
 - tokens: (List[str]): List of the tokens in the sentence
 - tsa_tags: (List[str]): List of the tags for each token in BIO format. There is no integer representation of these in the dataset.
 
 
-
-
 ### Data Splits
 ```
 DatasetDict({
@@ -155,80 +142,52 @@ DatasetDict({
 })
 ```
 
-## Dataset Creation
-
-### Curation Rationale
-The sentiment expressions and targets are annotated in NoReC_fine according to its  [annotation guidelines](https://github.com/ltgoslo/norec_fine/blob/master/annotation_guidelines/guidelines.md)
-
-Since a sentiment target may be the target of several sentiment expressions, these are resolved to a final sentiment polarity (and intensity) using the conversion script in [NoReC_tsa](https://github.com/ltgoslo/norec_tsa). There is no "mixed" sentiment category. When a target is the receiver of both positive and negative sentiment, the strongest wins. If a tie, the last sentiment wins. 
 
+## Dataset Creation
 ### Source Data
-A subset of the Norwegian Review Corpus with its sources and preprocessing described [here](https://github.com/ltgoslo/norec).
 
-<!---
-#### Initial Data Collection and Normalization
+The sentiment annotations are aggregated from the NoReC_fine dataset, which in turn comprises a subset of the documents in the [Norwegian Review Corpus](https://github.com/ltgoslo/norec) (NoReC), which contains full-text professional reviews collected from major Norwegian news sources and cover a range of different domains, including literature, movies, video games, restaurants, music and theater, in addition to product reviews across a range of categories. The review articles NoReC were originally donated by the media partners in the SANT project; the Norwegian Broadcasting Corporation (NRK), Schibsted Media Group and Aller Media. The data comprises reviews extracted from eight different Norwegian news sources: Dagbladet, VG, Aftenposten, Bergens Tidende, Fædrelandsvennen, Stavanger Aftenblad, DinSide.no and P3.no. In terms of publishing date the reviews of NoReC mainly cover the time span 2003–2019, although it also includes a handful of reviews dating back as far as 1998.
 
-[More Information Needed]
+### Annotators
 
-#### Who are the source language producers?
+The original annotations of NoReC_fine that the sentence-level labels here are derived from, were originally created by hired annotators who were all BSc- or MSc-level students in the Language Technology study program at the Department of informatics, University of Oslo. 
 
-[More Information Needed]
+#### Personal and Sensitive Information
 
-### Annotations
+<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
 
-#### Annotation process
+The data does not contain information considered personal or sensitive.
 
-[More Information Needed]
+### Recommendations
 
-#### Who are the annotators?
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
 
-[More Information Needed]
+Results obtained on this data might not generalize to texts from other domains or genres. Any biases in the sentiments expressed by the original review authors may carry over to models trained on this data.
 
-### Personal and Sensitive Information
-
-[More Information Needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed]
---->
-### Discussion of Biases
-The professional review texts in NoReC that NoReC_tsa is a subset from, are from a set number of Norwegian Publishing channels and from a set timespan that can be explored in the [NoReC metadata](https://raw.githubusercontent.com/ltgoslo/norec/master/data/metadata.json). Both language usage and sentiments expressed could have been more diverse with a more diverse set of source texts.
-
-<!---
-### Other Known Limitations
-
-[More Information Needed]
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed]
---->
-### Licensing Information
-
-The data, being derived from [NoReC](https://github.com/ltgoslo/norec), is distributed under a Creative Commons Attribution-NonCommercial licence (CC BY-NC 4.0), access the full license text here: https://creativecommons.org/licenses/by-nc/4.0/
+## Citation
+**BibTeX:**
+```
+@InProceedings{KutBarVel21,
+  author = {Andrey Kutuzov and Jeremy Barnes and Erik Velldal and Lilja {\O}vrelid and Stephan Oepen}, 
+  title = {Large-Scale Contextualised Language Modelling for Norwegian},
+  booktitle = {{Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa 2021)}},
+  year = 2021
+}
 
-The licence is motivated by the need to block the possibility of third parties redistributing the orignal reviews for commercial purposes. Note that machine learned models, extracted lexicons, embeddings, and similar resources that are created on the basis of NoReC are not considered to contain the original data and so can be freely used also for commercial purposes despite the non-commercial condition.
+@InProceedings{OvrMaeBar20,
+  author = {Lilja {\O}vrelid and Petter M{\ae}hlum and Jeremy Barnes and Erik Velldal},
+  title = {A Fine-grained Sentiment Dataset for {N}orwegian},
+  booktitle = {{Proceedings of the 12th Edition of the Language Resources and Evaluation Conference}},
+  year = 2020,
+  address = "Marseille, France, 2020"
+}
+```
+## Dataset Card Authors
 
+Egil Rønningstad and Erik Velldal
 
-### Citation Information
+## Dataset Card Contact
 
-```bibtex
-@InProceedings{OvrMaeBar20,   
-author = {Lilja Øvrelid and Petter Mæhlum and Jeremy Barnes and Erik Velldal},   
-title = {A Fine-grained Sentiment Dataset for {N}orwegian}, 
-booktitle = {{Proceedings of the 12th Edition of the Language Resources and Evaluation Conference}},  
-year = 2020,  
-address = {Marseille, France, 2020} 
-}
-```
+egilron@ifi.uio.no and erikve@ifi.uio.no
 
-<!---
-### Contributions
 
-[More Information Needed]
---->