Developing a Russian Database of Regular Semantic Relations Based on Word Embeddings

Page 799-809
Author Ekaterina Enikeeva, Andrey Popov
Title Developing a Russian Database of Regular Semantic Relations Based on Word Embeddings
Abstract Recent computational semantic models yield high-quality results with regard to semantic relations extraction tasks, and thus may be applied as a baseline for semantic lexicon construction. Moreover, the stochastic information about lexical compatibility is useful for reducing ambiguity and detecting anomalies during syntactic parsing. We prove that this approach is reasonable and describe a Russian semantic lexical database, acquired in an unsupervised manner and employed as a semantic component of a syntactic parser and a fact extraction system.
Session Poster Presentations
Keywords distributional semantics, word vector representations, semantic lexicon, Meaning ? Text model
BibTex 
@InProceedings{ELX2018-065,
	author={Ekaterina Enikeeva, Andrey Popov},
	title={Developing a Russian Database of Regular Semantic Relations Based on Word Embeddings},
	pages={799-809},
	booktitle={Proceedings of the XVIII EURALEX International Congress: Lexicography in Global Contexts},
	year={2018},
	month={jul},
	date={17-21},
	address={Ljubljana, Slovenia},
	editor={Jaka Čibej, Vojko Gorjanc, Iztok Kosem, Simon Krek},
	publisher={Ljubljana University Press, Faculty of Arts},
	isbn={978-961-06-0097-8}, }
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