metadata

languages:
  - ca

TECA: Textual Entailment Catalan dataset

BibTeX citation

If you use any of these resources (datasets or models) in your work, please cite our latest paper:

@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",
}

Digital Object Identifier (DOI) and access to dataset files

Introduction

TECA consists of two subsets of textual entailment in Catalan, catalan_TE1 and vilaweb_TE, which contain 14997 and 6166 pairs of premises and hypotheses, annotated according to the inference relation they have (implication, contradiction or neutral).

This dataset was developed by BSC TeMU as part of the AINA project and intended as part of the Catalan Language Understanding Benchmark (CLUB). It is part of the Catalan Language Understanding Benchmark (CLUB) as presented in:

Armengol-Estapé J., Carrino CP., Rodriguez-Penagos C., de Gibert Bonet O., Armentano-Oller C., Gonzalez-Agirre A., Melero M., and Villegas M., Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan". Findings of ACL 2021 (ACL-IJCNLP 2021).

Supported Tasks and Leaderboards

Text classification, Language Model

Languages

CA- Catalan

Directory structure

.gitattributes
README.md
dev.json - json-formatted file with the dev split of the dataset
teca.py - data loader script
test.json - json-formatted file with the test split of the dataset
train.json - json-formatted file with the train split of the dataset

Dataset Structure

Data Instances

Two JSON files, one for each subset.

Example:

{
"id": 6940,
"premise": "Podriem posar uns bons filtres a les xemeneies de les quimiques per tal de que poguin seguint havent"hypothesis": "Caldria eliminar tots els filtres de les xemeneies de les qu\u00edmiques.",
"label": "2"
}

Number of sentence pairs

catalan_TE1: 14,997
vilaweb_TE: 6,166

Dataset Creation

Methodology

catalan_TE1: 12000 sentences were chosen randomly from the BSC Catalan Textual Corpus, and filtered by different criteria, such as length and stand-alone intelligibility. From 6000 text sentences, we commissioned 3 hypotheses (one for each entailment category) to be written by a team of annotators.

vilaweb_TE: We randomly selected 6200 headers from the Catalan news site Vilaweb and filtered them to obtain 2100 text sentences. For each text, 3 hypotheses were likewise commissioned.

Curation Rationale

In both sub-datasets, some sentence pairs were excluded because of inconsistencies.

Source Data

Initial Data Collection and Normalization

Source sentences are extracted from the Catalan Textual Corpus, and from Vilaweb newswire.

Annotations

Inter-annotator agreement:

From 600 randomly selected samples, the inter-annotator agreement was 83,57%.

Dataset Curators

Casimiro Pio Carrino, Carlos Rodríguez and Carme Armentano, from BSC-CNS.

Personal and Sensitive Information

No personal or sensitive information is included.

Contact

Carlos Rodríguez-Penagos ([email protected])
Carme Armentano-Oller ([email protected])

License

This work is licensed under an Attribution-NonCommercial-NoDerivatives 4.0 International License.