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arXiv · 1701.02962

Distinguishing Antonyms and Synonyms in a Pattern-based Neural Network

Kim Anh Nguyen·Sabine Schulte im Walde·Ngoc Thang Vu
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Abstract

Distinguishing between antonyms and synonyms is a key task to achieve high performance in NLP systems. While they are notoriously difficult to distinguish by distributional co-occurrence models, pattern-based methods have proven effective to differentiate between the relations. In this paper, we present a novel neural network model AntSynNET that exploits lexico-syntactic patterns from syntactic parse trees. In addition to the lexical and syntactic information, we successfully integrate the distance between the related words along the syntactic path as a new pattern feature. The results from classification experiments show that AntSynNET improves the performance over prior pattern-based methods.

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Kim Anh Nguyen, Sabine Schulte im Walde, Ngoc Thang Vu. 2017-01-11. Distinguishing Antonyms and Synonyms in a Pattern-based Neural Network. https://arxiv.org/abs/1701.02962

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