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languages: |
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- ca |
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# Semantic Textual Similarity in Catalan |
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## BibTeX citation |
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If you use any of these resources (datasets or models) in your work, please cite our latest paper: |
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```bibtex |
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@inproceedings{armengol-estape-etal-2021-multilingual, |
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title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan", |
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author = "Armengol-Estap{\'e}, Jordi and |
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Carrino, Casimiro Pio and |
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Rodriguez-Penagos, Carlos and |
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de Gibert Bonet, Ona and |
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Armentano-Oller, Carme and |
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Gonzalez-Agirre, Aitor and |
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Melero, Maite and |
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Villegas, Marta", |
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booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021", |
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month = aug, |
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year = "2021", |
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address = "Online", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2021.findings-acl.437", |
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doi = "10.18653/v1/2021.findings-acl.437", |
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pages = "4933--4946", |
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} |
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``` |
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## Digital Object Identifier (DOI) and access to dataset files |
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https://doi.org/10.5281/zenodo.4529184 |
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## Introduction |
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STS corpus is a benchmark for evaluating Semantic Text Similarity in Catalan. |
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It consists of more than 3000 sentence pairs, annotated with the semantic similarity between them, using a scale from 0 (no similarity at all) to 5 (semantic equivalence). It is done manually by 4 different annotators following our guidelines based on previous work from the SemEval challenges (https://www.aclweb.org/anthology/S13-1004.pdf). |
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The source data are scraped sentences from the Catalan Textual Corpus (https://doi.org/10.5281/zenodo.4519349), used under CC-by-SA-4.0 licence (https://creativecommons.org/licenses/by-sa/4.0/). The dataset is released under the same licence. |
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This dataset was developed by BSC TeMU as part of the AINA project, to enrich the Catalan Language Understanding Benchmark (CLUB). |
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This is the version 1.0.1 of the dataset with the complete human and automatic annotations, as well as the QA analysis scripts. It also has a more accurate license. |
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This dataset can be used to build and score semantic similarity models. |
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### Supported Tasks and Leaderboards |
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Semantic textual similiarity, Language Model |
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### Languages |
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CA - Catalan |
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### Directory structure |
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* dev.tsv |
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* sts-ca.py |
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* test.tsv |
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* train.tsv |
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* README |
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## Dataset Structure |
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### Data Instances |
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Follows SemEval challenges (https://www.aclweb.org/anthology/S13-1004.pdf). |
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### Data Fields |
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SemEval challenges formats and conventions (https://www.aclweb.org/anthology/S13-1004.pdf). |
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### Example: |
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| index | id | sentence 1 | sentence 2 | avg | |
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| ------- | ---- | ------------ | ------------ | ----- | |
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| 19 | ACN2_131 | Els manifestants ocupen l'Imperial Tarraco durant una hora fent jocs de taula | Els manifestants ocupen l'Imperial Tarraco i fan jocs de taula | 4 | |
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| 21 | TE2_80 | El festival comptarà amb cinc escenaris i se celebrarà entre el 7 i el 9 de juliol al Parc del Fòrum. | El festival se celebrarà el 7 i 8 de juliol al Parc del Fòrum de Barcelona | 3 | |
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| 23 | Oscar2_609 | Aleshores hi posarem un got de vi i continuarem amb la cocció fins que s'hagi evaporat el vi i ho salpebrarem. | Mentre, hi posarem el vi al sofregit i deixarem coure uns 7/8′, fins que el vi s'evapori. | 3 | |
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| 25 | Viqui2_48 | L'arboç grec (Arbutus andrachne) és un arbust o un petit arbre dins la família ericàcia. | El ginjoler ("Ziziphus jujuba") és un arbust o arbre petit de la família de les "Rhamnaceae". | 2.75 | |
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| 27 | ACN2_1072 | Mentre han estat davant la comandància, els manifestants han cridat consignes a favor de la independència i han cantat cançons com 'L'estaca'. | Entre les consignes que han cridat s'ha pogut escoltar càntics com 'els carrers seran sempre nostres' i contínues consignes en favor de la independència. | 3 | |
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| 28 | Viqui2_587 | Els cinc municipis ocupen una superfície de poc més de 100 km2 i conjuntament sumen una població total aproximada de 3.691 habitants (any 2019). | Té una població d'1.811.177 habitants (2005) repartits en 104 municipis d'una superfície total de 14.001 km2. | 2.67 | |
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### Data Splits |
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* sts_cat_dev_v1.tsv (493 annotated pairs) |
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* sts_cat_train_v1.tsv (492 annotated pairs) |
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* sts_cat_test_v1.tsv (2043 annotated pairs) |
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## Dataset Creation |
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### Methodology |
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Random sentences were extracted from 3 Catalan corpus: ACN, Oscar and Wikipedia, and we generated candidate pairs using a combination of metrics from Doc2Vec, Jaccard and a BERT-like model (“distiluse-base-multilingual-cased-v2”, [link](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. |
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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. |
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### Curation Rationale |
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For compatibility with similar datasets in other languages, we followed as close as possible existing curation guidelines. |
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### Source Data |
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#### Initial Data Collection and Normalization |
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The source data are scraped sentences from the Catalan Textual Corpus. |
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#### Who are the source language producers? |
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The Catalan Textual Corpus is a 1760-million-token web corpus of Catalan built from several sources: existing corpus such as DOGC, CaWac (non-dedup version), Oscar (unshuffled version), Open Subtitles, Catalan Wikipedia; and three brand new crawlings: the Catalan General Crawling, obtained by crawling the 500 most popular .cat and .ad domains; the Catalan Government Crawling, obtained by crawling the .gencat domain and subdomains, belonging to the Catalan Government; and the ACN corpus with 220k news items from March 2015 until October 2020, crawled from the Catalan News Agency. |
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### Annotations |
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#### Annotation process |
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We comissioned the manual annotation of the similiarity between the sentences of each pair, following the provided guidelines. |
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#### Who are the annotators? |
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A team of native language speakers from 2 different companies, working independently. |
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### Dataset Curators |
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Carlos Rodríguez and Carme Armentano, from BSC-CNS |
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### Personal and Sensitive Information |
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No personal or sensitive information included. |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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[More Information Needed] |
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### Discussion of Biases |
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[More Information Needed] |
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### Other Known Limitations |
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[More Information Needed] |
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## Contact |
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Carlos Rodríguez-Penagos ([email protected]) and Carme Armentano-Oller ([email protected]) |
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## License |
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<a rel="license" href="https://creativecommons.org/licenses/by-sa/4.0/"><img alt="Attribution-ShareAlike 4.0 International License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />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>. |
