A tool for effective extraction of synsets and semantic relations from BabelNet

DOI:	https://doi.org/10.1109/SSDSE.2017.8071954
URL:	https://www.researchgate.net/publication/320662537...
Additional URL:	http://ieeexplore.ieee.org/document/8071954/?reloa...
Document Type:	Conference or workshop publication
Year of publication:	2017
Book title:	2017 SSDSE : 2017 Siberian Symposium on Data Science and Engineering (SSDSE) : Novosibirsk, Akademgorodok, Russia, 12-13 Apr 2017
Page range:	10-13
Conference title:	2017 Siberian Symposium on Data Science and Engineering (SSDSE)
Location of the conference venue:	Novosibirsk, Russia
Date of the conference:	April 12-13, 2017
Publisher:	Goncharov, Sergey
Place of publication:	Piscataway, NJ
Publishing house:	IEEE
ISBN:	978-1-5386-1594-2 , 978-1-5386-1593-5 , 978-1-5386-1592-8
Publication language:	English
Institution:	School of Business Informatics and Mathematics > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
Subject:	004 Computer science, internet
Abstract:	Evaluation experiments in natural language processing often involve construction of samples from large lexical semantic resources, such as WordNet, Wiktionary, and OmegaWiki for evaluation and training purposes. The two most recurrent tasks are extraction of synsets and semantic relations between words. BabelNet is a resource which combines and interlinks all main lexical resources providing a unified assess to them. In this paper, we present BabelNet Extract, an open source tool which helps in addressing these two recurrent extraction tasks effectively in a parallelized manner from the large-scale multilingual BabelNet semantic network. The tool extracts individual word senses and the synsets they form as well as the semantic relations established between the synsets. We show its architecture, describe the output format, and discuss the use cases of the tool.