Distinguishing general concepts from individuals: an automatic coarse-grained classifier
| Data(s) |
2008
|
|---|---|
| Resumo |
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. |
| Identificador |
http://serval.unil.ch/?id=serval:BIB_3A11097C08BE http://ekaw2008.inrialpes.fr/EKAW2008PosterDemoProceedings.pdf |
| Idioma(s) |
en |
| Publicador |
EKAW 2008 |
| Fonte |
16th International conference on knowledge engineering and knowledge management knowledge patterns, Acitrezza, 2008. Poster and demo proceedings |
| Tipo |
info:eu-repo/semantics/conferenceObject inproceedings |
