From syntactic structure to semantic relationship: hypernym extraction from definitions by recurrent neural networks using the part of speech information

Yixin Tan; Xiaomeng Wang; Tao Jia

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arXiv · 2012.03418

From syntactic structure to semantic relationship: hypernym extraction from definitions by recurrent neural networks using the part of speech information

Yixin Tan·Xiaomeng Wang·Tao Jia

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Abstract

The hyponym-hypernym relation is an essential element in the semantic network. Identifying the hypernym from a definition is an important task in natural language processing and semantic analysis. While a public dictionary such as WordNet works for common words, its application in domain-specific scenarios is limited. Existing tools for hypernym extraction either rely on specific semantic patterns or focus on the word representation, which all demonstrate certain limitations.

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Yixin Tan, Xiaomeng Wang, Tao Jia. 2020-12-07. From syntactic structure to semantic relationship: hypernym extraction from definitions by recurrent neural networks using the part of speech information. https://arxiv.org/abs/2012.03418

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