--- annotations_creators: - expert-generated language_creators: - found language: - ca license: - cc-by-nc-nd-4.0 multilinguality: - monolingual size_categories: - unknown source_datasets: [] task_categories: - text-classification task_ids: - natural-language-inference pretty_name: teca dataset_info: features: - name: version dtype: string - name: data list: - name: id dtype: string - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 3235471 num_examples: 1 - name: validation num_bytes: 405393 num_examples: 1 - name: test num_bytes: 401094 num_examples: 1 download_size: 2027427 dataset_size: 4041958 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* --- # Dataset Card for TE-ca ## Dataset Description - **Website:** https://zenodo.org/record/4761458 - **Repository** [HuggingFace](https://huggingface.co/projecte-aina) - **Paper:** [Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan](https://arxiv.org/abs/2107.07903) - **Point of Contact:** [Language Technologies Unit](langtech@bsc.es) ### Dataset Summary TE-ca is a dataset of textual entailment in Catalan, which contains 21,163 pairs of premises and hypotheses, annotated according to the inference relation they have (implication, contradiction or neutral). This dataset was developed by [BSC TeMU](https://temu.bsc.es/) as part of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina/), to enrich the [Catalan Language Understanding Benchmark (CLUB)](https://club.aina.bsc.es/). This work is licensed under an Attribution-NonCommercial-NoDerivatives 4.0 International License. ### Supported Tasks and Leaderboards Textual entailment, Text classification, Language Model ### Languages The dataset is in Catalan (`ca-ES`). ## Dataset Structure ### Data Instances Three JSON files, one for each split. ### Example:
{ "id": 3247, "premise": "L'ONU adopta a Marràqueix un pacte no vinculant per les migracions", "hypothesis": "S'acorden unes recomanacions per les persones migrades a Marràqueix", "label": "0" }, { "id": 2825, "premise": "L'ONU adopta a Marràqueix un pacte no vinculant per les migracions", "hypothesis": "Les persones migrades seran acollides a Marràqueix", "label": "1" }, { "id": 2431, "premise": "L'ONU adopta a Marràqueix un pacte no vinculant per les migracions", "hypothesis": "L'acord impulsat per l'ONU lluny de tancar-se", "label": "2" },### Data Fields - premise: text - hypothesis: text related to the premise - label: relation between premise and hypothesis: * 0: entailment * 1: neutral * 2: contradiction ### Data Splits * dev.json: 2116 examples * test.json: 2117 examples * train.json: 16930 examples ## Dataset Creation ### Curation Rationale We created this dataset to contribute to the development of language models in Catalan, a low-resource language. ### Source Data Source sentences are extracted from the [Catalan Textual Corpus](https://doi.org/10.5281/zenodo.4519349) and from [VilaWeb](https://www.vilaweb.cat) newswire. #### Initial Data Collection and Normalization 12000 sentences from the BSC [Catalan Textual Corpus](https://doi.org/10.5281/zenodo.4519349), together with 6200 headers from the Catalan news site [VilaWeb](https://www.vilaweb.cat), were chosen randomly. We filtered them by different criteria, such as length and stand-alone intelligibility. For each selected text, we commissioned 3 hypotheses (one for each entailment category) to be written by a team of native annotators. Some sentence pairs were excluded because of inconsistencies. #### Who are the source language producers? The Catalan Textual Corpus corpus consists of several corpora gathered from web crawling and public corpora. More information can be found [here](https://doi.org/10.5281/zenodo.4519349). [VilaWeb](https://www.vilaweb.cat) is a Catalan newswire. ### Annotations #### Annotation process We commissioned 3 hypotheses (one for each entailment category) to be written by a team of annotators. #### Who are the annotators? Annotators are a team of native language collaborators from two independent companies. ### Personal and Sensitive Information No personal or sensitive information included. ## Considerations for Using the Data ### Social Impact of Dataset We hope this dataset contributes to the development of language models in Catalan, a low-resource language. ### Discussion of Biases [N/A] ### Other Known Limitations [N/A] ## Additional Information ### Dataset Curators Text Mining Unit (TeMU) at the Barcelona Supercomputing Center (bsc-temu@bsc.es) This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina). ### Licensing Information This work is licensed under an Attribution-NonCommercial-NoDerivatives 4.0 International License. ### 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.4529183)