update readme

README.md

@@ -1,11 +1,11 @@
 ---
-language:
+language: &id001
 - 'no'
 license: cc
-size_categories:
+size_categories: &id002
 - 10K<n<100K
 pretty_name: NoReC
-configs:
+configs: &id003
 - config_name: default
   data_files:
   - split: train
@@ -15,84 +15,97 @@ configs:
   - split: test
     path: data/test-*
 dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: split
-    dtype: string
-  - name: rating
-    dtype: int64
-  - name: category
-    dtype: string
-  - name: day
-    dtype: int64
-  - name: month
-    dtype: int64
-  - name: year
-    dtype: int64
-  - name: excerpt
-    dtype: string
-  - name: language
-    dtype: string
-  - name: source
-    dtype: string
-  - name: authors
-    dtype: string
-  - name: title
-    dtype: string
-  - name: url
-    dtype: string
-  - name: text
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 94334212
-    num_examples: 34749
-  - name: validation
-    num_bytes: 13597517
-    num_examples: 4348
-  - name: test
-    num_bytes: 13787751
-    num_examples: 4340
-  download_size: 77286913
-  dataset_size: 121719480
+  language: *id001
+  license: cc
+  size_categories: *id002
+  pretty_name: NoReC
+  configs: *id003
+  dataset_info:
+    features:
+    - name: id
+      dtype: string
+    - name: split
+      dtype: string
+    - name: rating
+      dtype: int64
+    - name: category
+      dtype: string
+    - name: day
+      dtype: int64
+    - name: month
+      dtype: int64
+    - name: year
+      dtype: int64
+    - name: excerpt
+      dtype: string
+    - name: language
+      dtype: string
+    - name: source
+      dtype: string
+    - name: authors
+      dtype: string
+    - name: title
+      dtype: string
+    - name: url
+      dtype: string
+    - name: text
+      dtype: string
+    splits:
+    - name: train
+      num_bytes: 94334212
+      num_examples: 34749
+    - name: validation
+      num_bytes: 13597517
+      num_examples: 4348
+    - name: test
+      num_bytes: 13787751
+      num_examples: 4340
+    download_size: 77286913
+    dataset_size: 121719480
+  homepage: https://github.com/ltgoslo/norec
+  citation: "@InProceedings{VelOvrBer18,\n  author = {Erik Velldal and Lilja {\\O}vrelid\
+    \ and \n            Eivind Alexander Bergem and  Cathrine Stadsnes and \n    \
+    \        Samia Touileb and Fredrik J{\\o}rgensen},\n  title = {{NoReC}: The {N}orwegian\
+    \ {R}eview {C}orpus},\n  booktitle = {Proceedings of the 11th edition of the \n\
+    \               Language Resources and Evaluation Conference},\n  year = {2018},\n\
+    \  address = {Miyazaki, Japan},\n  pages = {4186--4191}\n}\n}"
 ---
 # NoReC: The Norwegian Review Corpus
-This repository distributes the Norwegian Review Corpus (NoReC), created for the purpose of training and evaluating models for document-level sentiment analysis. 
+This is the official repository distributes the Norwegian Review Corpus (NoReC), created for the purpose of training and evaluating models for document-level sentiment analysis. 
 More than 43,000 full-text reviews have been 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. Each review is labeled with a manually assigned score of 1–6, as provided by the rating of the original author. The accompanying [paper](http://www.lrec-conf.org/proceedings/lrec2018/pdf/851.pdf) by Velldal et al. at LREC 2018 describes the (initial release of the) data in more detail. 
 
-id, split, rating, category, day, month, year, excerpt, language, source, authors, title, url, text
+## Dataset details
+- **The columns are:**
+`id, split, rating, category, day, month, year, excerpt, language, source, authors, title, url, text` where basic usage has `text` as the input and `rating` as the output.
 
 
-
-
-- **Curated by:** [More Information Needed]
 - **Funding:** 
 NoReC was created as part of the [SANT](https://www.mn.uio.no/ifi/english/research/projects/sant/) project (Sentiment Analysis for Norwegian Text),
 a collaboration between the Language Technology Group (LTG) at the Department of Informatics at the University of Oslo, the Norwegian Broadcasting Corporation (NRK), Schibsted Media Group and Aller Media.
 
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** Norwegian Bokmål (nb) and Norwegian Nynorsk (nn)
-- **License:** 
+
+- **Language(s):** Norwegian Bokmål (nb) and Norwegian Nynorsk (nn)
+- **License:** [See the license for the NoReC corpus](https://github.com/ltgoslo/norec), copied here for convenience:
 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. 
 
-### Dataset Sources [optional]
+- **Dataset Sources** 
 This verion of the corpus comprises 43,436 review texts extracted from eight different news sources: Dagbladet, VG, Aftenposten, Bergens Tidende, Fædrelandsvennen, Stavanger Aftenblad, DinSide.no and P3.no.
 <!-- Provide the basic links for the dataset. -->
 
-- **Repository:** https://github.com/ltgoslo/norec.git
-- **Paper [optional]:**  The accompanying paper by Velldal et al. at LREC 2018 describes the (initial release of the) data in more detail.
+- **Repository:** https://github.com/ltgoslo/norec
+- **Paper :**  [The accompanying paper by Velldal et al. at LREC 2018](http://www.lrec-conf.org/proceedings/lrec2018/pdf/851.pdf) describes the (initial release of the) data in more detail.
 
 
 ## Uses
 
-The dataset is intended for document-level sentiment analysis, to learn to predict the rating from the text. The field "category" can be considered til "domain" of each text. By filtering in and out category values, one may inspect cross-domain performance of a model.
+The dataset is intended for document-level sentiment analysis, to learn to predict the `rating` from the `text`. The field `category` can be considered the "domain" of each text. By filtering in and out `category` values, one may inspect cross-domain performance of a model. The other fields contain metadata preserved from the original version of the dataset, and may be used for further filtering and analyses.
 
 
 ## Source Data
-This _2nd release, v.2.1_ of the corpus comprises 43,436 review texts extracted from eight different news sources: Dagbladet, VG, Aftenposten, Bergens Tidende, Fædrelandsvennen, Stavanger Aftenblad, DinSide.no and P3.no. 
+This _2nd release, v.2.1_ of the corpus comprises 43,436 review texts extracted from eight different news sources: Dagbladet (db), VG (vg), Aftenposten (ap), Bergens Tidende (bt), Fædrelandsvennen (fvn), Stavanger Aftenblad (sa), DinSide.no (dinside) and P3.no (p3).  
+
 In terms of publishing date the reviews mainly cover the time span 2003–2019, although it also includes a handful of reviews dating back as far as 1998.
 
 
@@ -138,78 +151,24 @@ All splits combined
 | train   |    1453 |         4337 |    156 |   11777 |       2771 |           745 |    12536 |      118 |     856 |   34749 |
 
 
-#### Data Collection and Processing
-
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
-
-#### Who are the source data producers?
-
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
-
-### Annotations [optional]
-
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-
-#### Annotation process
-
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
-
-#### Personal and Sensitive Information
-
-<!-- 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. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## 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]
+## Citation
 
-[More Information Needed]
+```
+@InProceedings{VelOvrBer18,
+  author = {Erik Velldal and Lilja {\O}vrelid and Eivind Alexander Bergem and  Cathrine Stadsnes and Samia Touileb and Fredrik J{\o}rgensen},
+  title = {{NoReC}: The {N}orwegian {R}eview {C}orpus},
+  booktitle = {Proceedings of the 11th edition of the 
+               Language Resources and Evaluation Conference},
+  year = {2018},
+  address = {Miyazaki, Japan},
+  pages = {4186--4191}
+}
+```
 
-## Dataset Card Authors [optional]
 
-[More Information Needed]
+## Dataset Card Authors
 
-## Dataset Card Contact
+https://huggingface.co/ltg
 
-[More Information Needed]