Update README.md

README.md

@@ -1,49 +1,65 @@
 ---
+annotations_creators:
+- expert-generated
+language_creators:
+- found
 languages:
-- ca
+- catalan
+licenses:
+- cc-by-4.0
+multilinguality:
+- monolingual
+pretty_name: ancora-ca-ner
+size_categories:
+- unknown
+source_datasets: []
+task_categories: []
+task_ids: []
 ---
 
-# Named Entites from Ancora Corpus
-
-## BibTeX  citation
-
-If you use any of these resources (datasets or models) in your work, please cite our latest paper:
-
-```bibtex
-@inproceedings{armengol-estape-etal-2021-multilingual,
-    title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
-    author = "Armengol-Estap{\'e}, Jordi  and
-      Carrino, Casimiro Pio  and
-      Rodriguez-Penagos, Carlos  and
-      de Gibert Bonet, Ona  and
-      Armentano-Oller, Carme  and
-      Gonzalez-Agirre, Aitor  and
-      Melero, Maite  and
-      Villegas, Marta",
-    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
-    month = aug,
-    year = "2021",
-    address = "Online",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/2021.findings-acl.437",
-    doi = "10.18653/v1/2021.findings-acl.437",
-    pages = "4933--4946",
-}
-```
-
-
-## Digital Object Identifier (DOI) and access to dataset files
-
-https://doi.org/10.5281/zenodo.4529299
+# Dataset Card Creation Guide
+
+## Table of Contents
+- [Dataset Card Creation Guide](#dataset-card-creation-guide)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+    - [Annotations](#annotations)
+      - [Annotation process](#annotation-process)
+      - [Who are the annotators?](#who-are-the-annotators)
+    - [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
 
 
-## Introduction
+- **Paper:** [Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan](https://arxiv.org/abs/2107.07903)
+- **Paper:** [AnCora: Multilevel Annotated Corpora for Catalan and Spanish](http://www.lrec-conf.org/proceedings/lrec2008/pdf/35_paper.pdf)
+- **Point of Contact:** Carlos Rodríguez-Penagos (carlos.rodriguez1@bsc.es) and Carme Armentano-Oller (carme.armentano@bsc.es)
 
-This is a dataset for Named Entity Recognition (NER) from <a href="http://clic.ub.edu/corpus/">Ancora corpus</a> adapted for Machine Learning and Language Model evaluation purposes.
+### Dataset Summary
 
-Since multiwords (including Named Entities) in the original Ancora corpus are aggregated as a single lexical item using underscores (e.g. "Ajuntament_de_Barcelona") we splitted them to align with word-per-line format, and added conventional <a href="https://en.wikipedia.org/wiki/Inside%E2%80%93outside%E2%80%93beginning_(tagging)">Begin-Inside-Outside (IOB) tags</a> to mark and classify Named Entities. We did not filter out the different categories of NEs from Ancora (weak and strong). We did 6 minor edits by hand.
+This is a dataset for Named Entity Recognition (NER) in Catalan. It adapts <a href="http://clic.ub.edu/corpus/">Ancora corpus</a> for Machine Learning and Language Model evaluation purposes.
 
-AnCora corpus is used under [CC-by] (https://creativecommons.org/licenses/by/4.0/) licence. 
+AnCora corpus is used under [CC-by](https://creativecommons.org/licenses/by/4.0/) licence. 
 
 This dataset was developed by BSC TeMU as part of the AINA project, and to enrich the Catalan Language Understanding Benchmark (CLUB). 
 
@@ -53,26 +69,14 @@ Named Entities Recognition, Language Model
 
 ### Languages
 
-CA- Catalan
-
-### Directory structure
- 
-* dev.txt
-* test.txt
-* train.txt
-
+CA - Catalan
 
 ## Dataset Structure
 
 ### Data Instances
 
-three two-column files, one for each split.
-
-### Data Fields
-
-Every file has two columns, with the word form or punctuation symbol in the first one and the corresponding IOB tag in the second one.
+Three two-column files, one for each split. 
 
-### Example:
 <pre>
     Fundació B-ORG
     Privada I-ORG
@@ -91,25 +95,34 @@ Every file has two columns, with the word form or punctuation symbol in the firs
     Firal I-LOC
 </pre>
 
+### Data Fields
+
+Every file has two columns, with the word form or punctuation symbol in the first one and the corresponding IOB tag in the second one.
+
 ### Data Splits
 
-One for each sub-dataset for train, evaluation and test.
+We took the original train, dev and test splits from the [UD version of the corpus] (https://huggingface.co/datasets/universal_dependencies)
+
+- train: 10,628 examples
+- validation: 1,427 examples
+- test: 1,526 examples
+
 
 ## Dataset Creation
 
 ### Methodology
 
 We adapted the NER labels from Ancora corpus to a word-per-line format. 
-Since multiwords in the original Ancora corpus are aggregated as a single lexical item using underscores (e.g. "Ajuntament_de_Barcelona") we splitted them to align with this format, and added conventional <a href="https://en.wikipedia.org/wiki/Inside%E2%80%93outside%E2%80%93beginning_(tagging)">Begin-Inside-Outside (IOB) tags</a> to mark and classify Named Entities. We did not filter out the different categories of NEs from Ancora (weak and strong). We did 6 minor edits by hand.
 
 ### Curation Rationale
 
+
 ### Source Data
 
 #### Initial Data Collection and Normalization
 
 AnCora consists of a Catalan corpus (AnCora-CA) and a Spanish corpus (AnCora-ES), each of them of 500,000 tokens (some multi-word). The corpora are annotated for linguistic phenomena at different levels.
-AnCora corpus is mainly based on newswire texts. For more information, refer to Taulé, M., M.A. Martí, M. Recasens (2009). “AnCora: Multilevel Annotated Corpora for Catalan and Spanish”, Proceedings of 6th International Conference on language Resources and Evaluation. http://www.lrec-conf.org/proceedings/lrec2008/pdf/35_paper.pdf
+AnCora corpus is mainly based on newswire texts. For more information, refer to Taulé, M., M.A. Martí, M. Recasens (2009). <a href="http://www.lrec-conf.org/proceedings/lrec2008/pdf/35_paper.pdf">"AnCora: Multilevel Annotated Corpora for Catalan and Spanish”, Proceedings of 6th International Conference on language Resources and Evaluation"</a>.
 
 #### Who are the source language producers?
 
@@ -124,12 +137,6 @@ We adapted the NER labels from Ancora corpus to a token-per-line, multi-column f
 #### Who are the annotators?
 
 Original annotators from Ancora corpus.
-
-
-### Dataset Curators
-
-Carlos Rodríguez and Carme Armentano, from BSC-CNS, did the conversion and curation.
-
 ### Personal and Sensitive Information
 
 No personal or sensitive information included.
@@ -148,13 +155,41 @@ No personal or sensitive information included.
 
 [More Information Needed]
 
+## Additional Information
+### Dataset Curators
 
-## Contact
-
-Carlos Rodríguez-Penagos (carlos.rodriguez1@bsc.es) and Carme Armentano-Oller (carme.armentano@bsc.es)
+Carlos Rodríguez and Carme Armentano, from BSC-CNS, did the conversion and curation.
 
-## License
+### Licensing information
 
 <a rel="license" href="https://creativecommons.org/licenses/by/4.0/"><img alt="Attribution 4.0 International License" style="border-width:0" src="https://chriszabriskie.com/img/cc-by.png" width="100"/></a><br />This work is licensed under a <a rel="license" href="https://creativecommons.org/licenses/by/4.0/">Attribution 4.0 International License</a>.
 
+### Citation Information
+
+```
+@inproceedings{armengol-estape-etal-2021-multilingual,
+    title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
+    author = "Armengol-Estap{\'e}, Jordi  and
+      Carrino, Casimiro Pio  and
+      Rodriguez-Penagos, Carlos  and
+      de Gibert Bonet, Ona  and
+      Armentano-Oller, Carme  and
+      Gonzalez-Agirre, Aitor  and
+      Melero, Maite  and
+      Villegas, Marta",
+    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
+    month = aug,
+    year = "2021",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2021.findings-acl.437",
+    doi = "10.18653/v1/2021.findings-acl.437",
+    pages = "4933--4946",
+}
+
+```
+
+[DOI](https://doi.org/10.5281/zenodo.4529299)
+
+