Unsupervised Sense-Aware Hypernymy Extraction

Autor:	Ustalov, D., Alexander Panchenko, Biemann, C., Ponzetto, S. P.
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	FOS: Computer and information sciences Computer Science - Computation and Language Computation and Language (cs.CL)
Zdroj:	Scopus-Elsevier
Popis:	In this paper, we show how unsupervised sense representations can be used to improve hypernymy extraction. We present a method for extracting disambiguated hypernymy relationships that propagates hypernyms to sets of synonyms (synsets), constructs embeddings for these sets, and establishes sense-aware relationships between matching synsets. Evaluation on two gold standard datasets for English and Russian shows that the method successfully recognizes hypernymy relationships that cannot be found with standard Hearst patterns and Wiktionary datasets for the respective languages. In Proceedings of the 14th Conference on Natural Language Processing (KONVENS 2018). Vienna, Austria
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91f979024417c8ffae0c84ccc20c8ab6 http://arxiv.org/abs/1809.06223 Zobrazit plný text záznamu