An Approach to Reduce Part of Speech Ambiguity Using Semantically Annotated Lexicon Definitions

DOI

10.2991/msie-13.2013.94How to use a DOI?

Keywords

Lesk algorithm, knowledge-based Word Sense Disambiguation, semantically annotated glosses, lexicon network, semantic signature, semantic similarity cost, POS ambiguity

Abstract

In computational linguistics, the problem of word-sense disambiguation (WSD) is a difficult one and methods using a flat topology of the tokens are not very effective. One solution to this is to use a Part of Speech (POS) tagger before starting the WSD process. However, POS taggers show their limitations when high precision tagging is required or large texts are processed. This paper presents a technique to reduce the POS ambiguity using semantic information. As benchmarks we use as following standard WSD corpuses: Senseval2, Senseval3 and Semcor. Moreover, we tested our approach on WordNet semantically tagged glosses for English and on our own semantically tagged lexicon glosses for Romanian language.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Andrei Minc
AU  - Tefan Diaconescu
PY  - 2013/11
DA  - 2013/11
TI  - An Approach to Reduce Part of Speech Ambiguity Using Semantically Annotated Lexicon Definitions
BT  - Proceedings of the 2nd International Conference on Management Science and Industrial Engineering
PB  - Atlantis Press
SP  - 439
EP  - 446
SN  - 1951-6851
UR  - https://doi.org/10.2991/msie-13.2013.94
DO  - 10.2991/msie-13.2013.94
ID  - Minc2013/11
ER  -