Distinguishing general concepts from individuals: an automatic coarse-grained classifier
Details
Serval ID
serval:BIB_3A11097C08BE
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Distinguishing general concepts from individuals: an automatic coarse-grained classifier
Title of the conference
16th International conference on knowledge engineering and knowledge management knowledge patterns, Acitrezza, 2008. Poster and demo proceedings
Organization
EKAW 2008
Publication state
Published
Issued date
2008
Pages
63-65
Language
english
Notes
Picca:2008db
Abstract
Named entity recognizers are unable to distinguish if a term is a general concept as "scientist" or an individual as "Einstein". In this paper we explore the possibility to reach this goal combining two basic approaches: (i) Super Sense Tagging (SST) and (ii) YAGO. Thanks to these two powerful tools we could automatically create a corpus set in order to train the SuperSense Tagger. The general F1 is over 76% and the model is publicly available.
Publisher's website
Create date
31/03/2009 14:24
Last modification date
20/08/2019 13:29
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