Update README.md

README.md

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 ### Dataset Summary
 
-STS corpus is a benchmark for evaluating Semantic Text Similarity in Catalan. This dataset was developed by [BSC TeMU](https://temu.bsc.es/) as part of the Projecte AINA, to enrich the [Catalan Language Understanding Benchmark (CLUB)](https://temu-bsc.github.io/catalan-language-understanding-benchmark/). 
+STS corpus is a benchmark for evaluating Semantic Text Similarity in Catalan. This dataset was developed by [BSC TeMU](https://temu.bsc.es/) as part of the [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina/), to enrich the [Catalan Language Understanding Benchmark (CLUB)](https://temu-bsc.github.io/catalan-language-understanding-benchmark/). 
 
 
 ### Supported Tasks and Leaderboards
@@ -80,21 +80,21 @@ This dataset follows [SemEval](https://www.aclweb.org/anthology/S13-1004.pdf) ch
 
 ## Dataset Creation
 
-### Methodology
-
-Random sentences were extracted from 3 Catalan corpus: [ACN](https://www.acn.cat/), [Oscar](https://oscar-corpus.com/) and [Wikipedia](https://ca.wikipedia.org/wiki/Portada), and we generated candidate pairs using a combination of metrics from Doc2Vec, Jaccard and a BERT-like model (“[distiluse-base-multilingual-cased-v2](https://huggingface.co/distilbert-base-multilingual-cased)”). Finally, we  manually reviewed the generated pairs to reject non-relevant pairs (identical or ungrammatical sentences, etc.) before providing them to the annotation team.
-
-The average of the four annotations was selected as a “ground truth” for each sentence pair, except when an annotator diverged in more than one unit from the average. In these cases, we discarded the divergent annotation and recalculated the average without it. We also discarded 45 sentence pairs because the annotators disagreed too much.
-
 ### Curation Rationale
 
-For compatibility with similar datasets in other languages, we followed as close as possible existing curation guidelines.
+We created this corpus to contribute to the development of language models in Catalan, a low-resource language.
 
 ### Source Data
 
 #### Initial Data Collection and Normalization
 
-The source data are scraped sentences from the [Catalan Textual Corpus](https://doi.org/10.5281/zenodo.4519348).
+Random sentences were extracted from 3 Catalan subcorpus: [ACN](https://www.acn.cat/), [Oscar](https://oscar-corpus.com/) and [Wikipedia](https://ca.wikipedia.org/wiki/Portada), as published in the [Catalan Textual Corpus](https://zenodo.org/record/4519349#.Ys_0PexBzOs).
+
+We generated candidate pairs using a combination of metrics from Doc2Vec, Jaccard and a BERT-like model (“[distiluse-base-multilingual-cased-v2](https://huggingface.co/distilbert-base-multilingual-cased)”). Finally, we  manually reviewed the generated pairs to reject non-relevant pairs (identical or ungrammatical sentences, etc.) before providing them to the annotation team.
+
+The average of the four annotations was selected as a “ground truth” for each sentence pair, except when an annotator diverged in more than one unit from the average. In these cases, we discarded the divergent annotation and recalculated the average without it. We also discarded 45 sentence pairs because the annotators disagreed too much.
+
+For compatibility with similar datasets in other languages, we followed as close as possible existing curation guidelines.
 
 #### Who are the source language producers?
 
@@ -118,7 +118,7 @@ No personal or sensitive information included.
 
 ### Social Impact of Dataset
 
-[N/A]
+We hope this corpus contributes to the development of language models in Catalan, a low-resource language.
 
 ### Discussion of Biases
 
@@ -134,6 +134,8 @@ No personal or sensitive information included.
 
 Carlos Rodríguez-Penagos (carlos.rodriguez1@bsc.es) and Carme Armentano-Oller (carme.armentano@bsc.es) from [BSC-CNS](https://www.bsc.es/).
 
+This work was funded by the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina/).
+
 ### Licensing Information
 
 This work is licensed under a <a rel="license" href="https://creativecommons.org/licenses/by-sa/4.0/">Attribution-ShareAlike 4.0 International License</a>.