WikiSense: Supersense tagging of Wikipedia named entities based WordNet

Joseph Chang, Richard Tzong Han Tsai, Jason S. Chang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

In this paper, we introduce a minimally supervised method for learning to classify named-entity titles in a given encyclopedia into broad semantic categories in an existing ontology. Our main idea involves using overlapping entries in the encyclopedia and ontology and a small set of 30 handed tagged parenthetic explanations to automatically generate the training data. The proposed method involves automatically recognizing whether a title is a named entity, automatically generating two sets of training data, and automatically building a classification model for training a classification model based on textual and non-textual features. We present WikiSense, an implementation of the proposed method for extending the named entity coverage of WordNet by sense tagging Wikipedia titles. Experimental results show WikiSense achieves accuracy of over 95% and near 80% applicability for all NE titles in Wikipedia. WikiSense cleanly produces over 1.2 million of NEs tagged with broad categories, based on the lexicographers' files of WordNet, effectively extending WordNet to form a very large scale semantic category, a potentially useful resource for many natural language related tasks.

Original languageEnglish
Title of host publicationPACLIC 23 - Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation
PublisherCity University of Hong Kong Press
Pages72-81
Number of pages10
ISBN (Print)9789624423198
StatePublished - 2009
Event23rd Pacific Asia Conference on Language, Information and Computation, PACLIC 23 - Hong Kong, China
Duration: 3 Dec 20095 Dec 2009

Publication series

NamePACLIC 23 - Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation
Volume1

Conference

Conference23rd Pacific Asia Conference on Language, Information and Computation, PACLIC 23
Country/TerritoryChina
CityHong Kong
Period3/12/095/12/09

Keywords

  • Semantic category
  • Wikipedia
  • Word sense disambiguation
  • WordNet

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