UAlberta at SemEval-2020 Task 2: Using Translations to Predict Cross-Lingual Entailment

Bradley Hauer, Amir Ahmad Habibi, Yixing Luan, Arnob Mallik, Grzegorz Kondrak


Abstract
We investigate the hypothesis that translations can be used to identify cross-lingual lexical entailment. We propose novel methods that leverage parallel corpora, word embeddings, and multilingual lexical resources. Our results demonstrate that the implementation of these ideas leads to improvements in predicting entailment.
Anthology ID:
2020.semeval-1.32
Volume:
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Month:
December
Year:
2020
Address:
Barcelona (online)
Editors:
Aurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
Venue:
SemEval
SIG:
SIGLEX
Publisher:
International Committee for Computational Linguistics
Note:
Pages:
263–269
Language:
URL:
https://aclanthology.org/2020.semeval-1.32
DOI:
10.18653/v1/2020.semeval-1.32
Bibkey:
Cite (ACL):
Bradley Hauer, Amir Ahmad Habibi, Yixing Luan, Arnob Mallik, and Grzegorz Kondrak. 2020. UAlberta at SemEval-2020 Task 2: Using Translations to Predict Cross-Lingual Entailment. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 263–269, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
UAlberta at SemEval-2020 Task 2: Using Translations to Predict Cross-Lingual Entailment (Hauer et al., SemEval 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.semeval-1.32.pdf
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