Update README.md

README.md

@@ -57,6 +57,14 @@ configs:
     path: ternary/validation-*
   - split: test
     path: ternary/test-*
+license: cc
+task_categories:
+- text-classification
+language:
+- 'no'
+pretty_name: NoReC_document
+size_categories:
+- 10K<n<100K
 ---
 
 # Dataset Card for NoReC_document
@@ -67,26 +75,17 @@ Document-level polarity classification of Norwegian full-text reviews across mix
 
 ## Dataset Details
 
-### Dataset Description
+This is a dataset for document-level sentiment classification in Norwegian, derived from the Norwegian Review Corpus: [NoReC](https://huggingface.co/datasets/ltg/norec). We here provive two simplified versions of NoReC where the original six-point numerical rating has been mapped to a recuced set of categorical classes: _positive_ and _negative_ for the binary version, and _positive_, _fair_, and _negative_ for the ternary version. The data comes with pre-defined splits for training, validataion, and testing.
 
-<!-- Provide a longer summary of what this dataset is. -->
-
-This is a dataset for document-level sentiment classification in Norwegian, derived from the Norwegian Review Corpus: [NoReC](https://github.com/ltgoslo/norec). We here provive two simplified versions of NoReC where the original six-point numerical rating has been mapped to a recuced set of categorical classes: _positive_ and _negative_ for the binary version, and _positive_, _fair_, and _negative_ for the ternary version. The data comes with pre-defined splits for training, validataion, and testing.
-
-- **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).
+- **Curated by:** The underlying NoReC data was created as part of the [SANT](https://www.mn.uio.no/ifi/english/research/projects/sant/) project (Sentiment Analysis for Norwegian Text), coordinated by the [Language Technology Group](https://www.mn.uio.no/ifi/english/research/groups/ltg/) (LTG) at the University of Oslo, in collaboration with the Norwegian Broadcasting Corporation (NRK), Schibsted Media Group and Aller Media.
+- **Funded by:** The [SANT](https://www.mn.uio.no/ifi/english/research/projects/sant/) project 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
-- **Language(s) (NLP):** Norwegian (Nokmål and Nynorsk)
-- **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.
-
-
-### Dataset Sources [optional]
+- **Language(s) (NLP):** Norwegian (Bokmål and Nynorsk)
+- **License:** The data 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/
+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. 
+- **Paper:**  [A paper by Velldal et al. at LREC 2018](http://www.lrec-conf.org/proceedings/lrec2018/pdf/851.pdf) describes the (initial release of the) underlying NoReC data in more detail.
 
-<!-- Provide the basic links for the dataset. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
 
 ## Uses
 
@@ -94,17 +93,6 @@ This is a dataset for document-level sentiment classification in Norwegian, deri
 
 The data is intended to be used for training and testing models for Norwegian document-level classification of polarity, either binary (positive / negative) or ternary (positive / fair / negative).
 
-### Direct Use
-
-<!-- This section describes suitable use cases for the dataset. -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
 
 ## Dataset Structure
 
@@ -112,19 +100,12 @@ The data is intended to be used for training and testing models for Norwegian do
 
 [More Information Needed]
 
-## Dataset Creation
-
-### Curation Rationale
-
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
 
 ### Source Data
 
 <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
 
-The document-level labels are dervied from 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.
+The document-level labels are derived from the [Norwegian Review Corpus](https://huggingface.co/datasets/ltg/norec) (NoReC), which contains over 43K 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.
 
 The numerical ratings of the underlying NoReC dataset were provided by the original review authors, i.e. these are the ratings assigned by professional journalists in the published versions of the review articles.
 
@@ -142,7 +123,7 @@ The data does not contain information considered personal or sensitive.
 
 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.
 
-## Citation [optional]
+## Citation
 
 <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
 
@@ -158,18 +139,6 @@ Results obtained on this data might not generalize to texts from other domains o
 }
 ```
 
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-
 ## Dataset Card Authors
 
 Vladislav Mikhailov and Erik Velldal