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

Autor:	Tan, Yixin, Wang, Xiaomeng, Jia, Tao
Rok vydání:	2020
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	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.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2012.03418 Zobrazit plný text záznamu View this record from Arxiv