BasqueGLUE: A Natural Language Understanding Benchmark for Basque

Gorka Urbizu, Iñaki San Vicente, Xabier Saralegi, Rodrigo Agerri, Aitor Soroa


Abstract
Natural Language Understanding (NLU) technology has improved significantly over the last few years and multitask benchmarks such as GLUE are key to evaluate this improvement in a robust and general way. These benchmarks take into account a wide and diverse set of NLU tasks that require some form of language understanding, beyond the detection of superficial, textual clues. However, they are costly to develop and language-dependent, and therefore they are only available for a small number of languages. In this paper, we present BasqueGLUE, the first NLU benchmark for Basque, a less-resourced language, which has been elaborated from previously existing datasets and following similar criteria to those used for the construction of GLUE and SuperGLUE. We also report the evaluation of two state-of-the-art language models for Basque on BasqueGLUE, thus providing a strong baseline to compare upon. BasqueGLUE is freely available under an open license.
Anthology ID:
2022.lrec-1.172
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
1603–1612
Language:
URL:
https://aclanthology.org/2022.lrec-1.172
DOI:
Bibkey:
Cite (ACL):
Gorka Urbizu, Iñaki San Vicente, Xabier Saralegi, Rodrigo Agerri, and Aitor Soroa. 2022. BasqueGLUE: A Natural Language Understanding Benchmark for Basque. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 1603–1612, Marseille, France. European Language Resources Association.
Cite (Informal):
BasqueGLUE: A Natural Language Understanding Benchmark for Basque (Urbizu et al., LREC 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2022.lrec-1.172.pdf
Code
 elhuyar/basqueglue