The (too Many) Problems of Analogical Reasoning with Word Vectors
Abstract
This paper explores the possibilities of analogical reasoning with vector space models. Given two pairs of words with the same relation (e.g. man:woman :: king:queen), it was proposed that the offset between one pair of the corresponding word vectors can be used to identify the unknown member of the other pair (king - man + woman = queen). We argue against such “linguistic regularities” as a model for linguistic relations in vector space models and as a benchmark, and we show that the vector offset (as well as two other, better-performing methods) suffers from dependence on vector similarity.- Anthology ID:
- S17-1017
- Volume:
- Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver, Canada
- Editors:
- Nancy Ide, Aurélie Herbelot, Lluís Màrquez
- Venue:
- *SEM
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 135–148
- Language:
- URL:
- https://aclanthology.org/S17-1017
- DOI:
- 10.18653/v1/S17-1017
- Cite (ACL):
- Anna Rogers, Aleksandr Drozd, and Bofang Li. 2017. The (too Many) Problems of Analogical Reasoning with Word Vectors. In Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017), pages 135–148, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- The (too Many) Problems of Analogical Reasoning with Word Vectors (Rogers et al., *SEM 2017)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/S17-1017.pdf