A French Corpus for Semantic SimilarityFrench Corpus for Semantic Similarity

Rémi Cardon, Natalia Grabar


Abstract
Semantic similarity is an area of Natural Language Processing that is useful for several downstream applications, such as machine translation, natural language generation, information retrieval, or question answering. The task consists in assessing the extent to which two sentences express or do not express the same meaning. To do so, corpora with graded pairs of sentences are required. The grade is positioned on a given scale, usually going from 0 (completely unrelated) to 5 (equivalent semantics). In this work, we introduce such a corpus for French, the first that we know of. It is comprised of 1,010 sentence pairs with grades from five annotators. We describe the annotation process, analyse these data, and perform a few experiments for the automatic grading of semantic similarity.
Anthology ID:
2020.lrec-1.851
Volume:
Proceedings of the 12th Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
6889–6894
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.851
DOI:
Bibkey:
Cite (ACL):
Rémi Cardon and Natalia Grabar. 2020. A French Corpus for Semantic SimilarityFrench Corpus for Semantic Similarity. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 6889–6894, Marseille, France. European Language Resources Association.
Cite (Informal):
A French Corpus for Semantic SimilarityFrench Corpus for Semantic Similarity (Cardon & Grabar, LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.851.pdf
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