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.
Original language | English |
---|---|
Title of host publication | Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (* SEM 2017) |
Number of pages | 14 |
Publication date | 2017 |
Pages | 135-148 |
Publication status | Published - 2017 |
Keywords
- Analogical Reasoning
- Vector Space Models
- Linguistic Relations
- Word Vectors
- Vector Similarity