Verb Sense Disambiguation Using Selectional Preferences Extracted with a State-of-the-art Semantic Role Labeler. Ye, P. & Baldwin, T. Technology, 2006.
abstract   bibtex   
This paper investigates whether multi- semantic-role (MSR) based selectional preferences can be used to improve the performance of supervised verb sense dis- ambiguation. Unlike conventional se- lectional preferences which are extracted from parse trees based on hand-crafted rules, and only include the direct subject or the direct object of the verbs, the MSR based selectional preferences to be pre- sented in this paper are extracted from the output of a state-of-the-art semantic role labeler and incorporate a much richer set of semantic roles. The performance of the MSR based selectional preferences is evaluated on two distinct datasets: the verbs from the lexical sample task of S ENSEVAL -2, and the verbs from a movie script corpus. We show that the MSR based features can indeed improve the per- formance of verb sense disambiguation.
@article{
 title = {Verb Sense Disambiguation Using Selectional Preferences Extracted with a State-of-the-art Semantic Role Labeler},
 type = {article},
 year = {2006},
 pages = {139-148},
 id = {99a46128-2ec2-3171-9d74-6678c75919db},
 created = {2012-04-01T16:32:49.000Z},
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 last_modified = {2017-03-14T14:36:19.698Z},
 tags = {semantic role labeling},
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 starred = {false},
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 abstract = {This paper investigates whether multi- semantic-role (MSR) based selectional preferences can be used to improve the performance of supervised verb sense dis- ambiguation. Unlike conventional se- lectional preferences which are extracted from parse trees based on hand-crafted rules, and only include the direct subject or the direct object of the verbs, the MSR based selectional preferences to be pre- sented in this paper are extracted from the output of a state-of-the-art semantic role labeler and incorporate a much richer set of semantic roles. The performance of the MSR based selectional preferences is evaluated on two distinct datasets: the verbs from the lexical sample task of S ENSEVAL -2, and the verbs from a movie script corpus. We show that the MSR based features can indeed improve the per- formance of verb sense disambiguation.},
 bibtype = {article},
 author = {Ye, Patrick and Baldwin, Timothy},
 journal = {Technology}
}
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