Semeval-2022 Task 1: CODWOE – Comparing Dictionaries and Word Embeddings

Timothee Mickus, Kees Van Deemter, Mathieu Constant, Denis Paperno


Abstract
Word embeddings have advanced the state of the art in NLP across numerous tasks. Understanding the contents of dense neural representations is of utmost interest to the computational semantics community. We propose to focus on relating these opaque word vectors with human-readable definitions, as found in dictionaries This problem naturally divides into two subtasks: converting definitions into embeddings, and converting embeddings into definitions. This task was conducted in a multilingual setting, using comparable sets of embeddings trained homogeneously.
Anthology ID:
2022.semeval-1.1
Volume:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
Month:
July
Year:
2022
Address:
Seattle, United States
Venues:
NAACL | SemEval
SIGs:
SIGSEM | SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–14
Language:
URL:
https://aclanthology.org/2022.semeval-1.1
DOI:
10.18653/v1/2022.semeval-1.1
Bibkey:
Cite (ACL):
Timothee Mickus, Kees Van Deemter, Mathieu Constant, and Denis Paperno. 2022. Semeval-2022 Task 1: CODWOE – Comparing Dictionaries and Word Embeddings. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 1–14, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
Semeval-2022 Task 1: CODWOE – Comparing Dictionaries and Word Embeddings (Mickus et al., SemEval 2022)
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PDF:
https://aclanthology.org/2022.semeval-1.1.pdf