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...
Weitere URL:	http://ieeexplore.ieee.org/document/8071954/?reloa...
Dokumenttyp:	Konferenzveröffentlichung
Erscheinungsjahr:	2017
Buchtitel:	2017 SSDSE : 2017 Siberian Symposium on Data Science and Engineering (SSDSE) : Novosibirsk, Akademgorodok, Russia, 12-13 Apr 2017
Seitenbereich:	10-13
Veranstaltungstitel:	2017 Siberian Symposium on Data Science and Engineering (SSDSE)
Veranstaltungsort:	Novosibirsk, Russia
Veranstaltungsdatum:	April 12-13, 2017
Herausgeber:	Goncharov, Sergey
Ort der Veröffentlichung:	Piscataway, NJ
Verlag:	IEEE
ISBN:	978-1-5386-1594-2 , 978-1-5386-1593-5 , 978-1-5386-1592-8
Sprache der Veröffentlichung:	Englisch
Einrichtung:	Fakultät für Wirtschaftsinformatik und Wirtschaftsmathematik > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
Fachgebiet:	004 Informatik
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.