Datasets:
carmentano
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README.md
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languages:
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---
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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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@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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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 can be used to build and score semantic similarity models.
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### Supported Tasks and Leaderboards
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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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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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| 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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#### 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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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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[More Information Needed]
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Carlos Rodríguez-Penagos ([email protected]) and Carme Armentano-Oller ([email protected])
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## License
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annotations_creators:
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- expert-generated
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language_creators:
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- found
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languages:
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- catalan
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licenses:
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- cc-by-4.0
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multilinguality:
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- monolingual
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pretty_name: sts-ca
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size_categories:
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- unknown
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source_datasets: []
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task_categories:
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- text-scoring
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task_ids:
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- semantic-similarity-scoring
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---
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# Semantic Textual Similarity in Catalan
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## Dataset Description
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- **Paper:** [Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan](https://arxiv.org/abs/2107.07903)
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- **Point of Contact:** Carlos Rodríguez-Penagos ([email protected]) and Carme Armentano-Oller ([email protected])
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### Dataset Summary
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STS corpus is a benchmark for evaluating Semantic Text Similarity in Catalan. 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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### Supported Tasks and Leaderboards
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This dataset can be used to build and score semantic similarity models in Catalan.
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### Languages
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CA - Catalan
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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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#### 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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| 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 Fields
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This dataset follows [SemEval](https://www.aclweb.org/anthology/S13-1004.pdf) challenges formats and conventions.
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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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#### Initial Data Collection and Normalization
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The source data are scraped sentences from the [Catalan Textual Corpus](https://doi.org/10.5281/zenodo.4519348).
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#### Who are the source language producers?
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A team of native language speakers from 2 different companies, working independently.
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### Personal and Sensitive Information
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No personal or sensitive information included.
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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Carlos Rodríguez-Penagos ([email protected]) and Carme Armentano-Oller ([email protected])
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### Licensing Information
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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>.
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### Citation Information
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```
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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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[DOI](https://doi.org/10.5281/zenodo.4529183)
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