Title
Extracting Ontological Selectional Preferences For Non-Pertainym Adjectives From The Google Corpus
Abstract
While there has been much research into using selectional preferences for word sense disambiguation (WSD), much difficulty has been encountered. To facilitate study into this difficulty and aid in WSD in general, a database of the selectional preferences of non-pertainym prenomial adjectives extracted from the Google Web IT 5-gram Corpus is proposed. A variety of methods for computing the preferences of each adjective over a set of noun categories from WordNet have been evaluated via simulated disambiguation of pseudo-homonyms. The best method of these involves computing for each noun category the ratio of single-word common (i.e. not proper) noun lemma types which can co-occur with a given adjective to the number of single-word common noun lemmata whose estimated frequency is greater than a threshold based on the frequency of the adjective. The database produced by this procedure will be made available to the public. Copyright © 2010, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Publication Date
1-1-2010
Publication Title
Proceedings of the National Conference on Artificial Intelligence
Volume
2
Number of Pages
1033-1038
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
77958519676 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/77958519676
STARS Citation
Tanner, John J. and Gomez, Fernando, "Extracting Ontological Selectional Preferences For Non-Pertainym Adjectives From The Google Corpus" (2010). Scopus Export 2010-2014. 1706.
https://stars.library.ucf.edu/scopus2010/1706