Update README.md

README.md

@@ -14,7 +14,7 @@ size_categories:
 - unknown
 source_datasets: []
 task_categories:
-- conditional-text-generation
+- summarization
 task_ids:
 - summarization
 ---
@@ -32,12 +32,20 @@ task_ids:
   - [Data Fields](#data-fields)
   - [Data Splits](#data-splits)
 - [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)
-  - [Funding](#funding)
-
+  - [Contributions](#contributions)
+  
 ## Dataset Description
 
 - **Paper:** [Sequence to Sequence Resources for Catalan](https://arxiv.org/pdf/2202.06871.pdf)
@@ -46,19 +54,18 @@ task_ids:
 
 ### Dataset Summary
 
-CaSum is a summarization dataset. It is extracted from a newswire corpus crawled from the Catalan News Agency. The corpus consists of 217,735 instances that are composed by the headline and the body.
+CaSum is a summarization dataset. It is extracted from a newswire corpus crawled from the [Catalan News Agency](https://www.acn.cat/). The corpus consists of 217,735 instances that are composed by the headline and the body.
  
 ### Supported Tasks and Leaderboards
 
-Summarization, Language Model
+- summarization: The dataset can be used to train a model for abstractive summarization. Success on this task is typically measured by achieving a high Rouge score. The [mbart-base-ca-casum](https://huggingface.co/projecte-aina/bart-base-ca-casum) model currently achieves a 41.39.
 
 ### Languages
 
-CA - Catalan
+The dataset is in Catalan (`ca-CA`).
 
 ## Dataset Structure
 
-
 ### Data Instances
 
 ```
@@ -68,7 +75,6 @@ CA - Catalan
 }
 ```
 
-
 ### Data Fields
 
 - `summary` (str): Summary of the piece of news
@@ -84,16 +90,61 @@ We split our dataset into train, dev and test splits
 
 ## Dataset Creation
 
-We obtained each headline and its corresponding body and applied the following cleaning pipeline: deduplicating the documents, removing the documents with empty attributes, and deleting some boilerplate sentences. 
+### Curation Rationale
+
+We created this corpus to contribute to the development of language models in Catalan, a low-resource language. There exist few resources for summarization in Catalan.
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+We obtained each headline and its corresponding body of each news piece on the [Catalan News Agency](https://www.acn.cat/) website and applied the following cleaning pipeline: deduplicating the documents, removing the documents with empty attributes, and deleting some boilerplate sentences. 
+
+#### Who are the source language producers?
+
+The news portal [Catalan News Agency](https://www.acn.cat/).
+
+### Annotations
+
+The dataset is unannotated.
+
+#### Annotation process
+
+[N/A]
+
+#### Who are the annotators?
+
+[N/A]
+
+### Personal and Sensitive Information
+
+Since all data comes from public websites, no anonymization process was performed.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+We hope this corpus contributes to the development of summarization models in Catalan, a low-resource language.
+
+### Discussion of Biases
+
+We are aware that since the data comes from unreliable web pages, some biases may be present in the dataset. Nonetheless, we have not applied any steps to reduce their impact.
+
+### Other Known Limitations
+
+[N/A]
 
 ## Additional Information
+
 ### Dataset Curators
 
-Ona de Gibert, Jordi Armengol-Estapé and Maite Melero, from BSC-CNS, did the conversion and curation.
+Ona de Gibert Bonet, Barcelona Supercomputing Center (ona.degibert@bsc.es)
+
+This work was funded by MT4All CEF project and the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya within the framework of the Aina project.
 
 ### Licensing information
 
-This work is licensed under a <a rel="license" href="https://creativecommons.org/licenses/by-nc/4.0/">Attribution-NonCommercial 4.0 International License</a>.
+[Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/).
 
 ### BibTeX  citation
 
@@ -110,6 +161,6 @@ If you use any of these resources (datasets or models) in your work, please cite
 }
 ```
 
-### Funding
+### Contributions
 
-This work was funded by the [MT4All CEF project](https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2019-eu-ia-0031) and the [Catalan Ministry of the Vice-presidency, Digital Policies and Territory](https://politiquesdigitals.gencat.cat/en/inici/index.html) within the framework of the [Aina project](https://politiquesdigitals.gencat.cat/ca/tic/aina-el-projecte-per-garantir-el-catala-en-lera-digital/).
+[N/A]