{"_id":"6QAukpbN2TwMWh6A7","bibbaseid":"ye-baldwin-verbsensedisambiguationusingselectionalpreferencesextractedwithastateoftheartsemanticrolelabeler-2006","authorIDs":[],"author_short":["Ye, P.","Baldwin, T."],"bibdata":{"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","file_attached":false,"profile_id":"5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6","group_id":"066b42c8-f712-3fc3-abb2-225c158d2704","last_modified":"2017-03-14T14:36:19.698Z","tags":"semantic role labeling","read":false,"starred":false,"authored":false,"confirmed":"true","hidden":false,"citation_key":"Ye2006a","private_publication":false,"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","bibtex":"@article{\n title = {Verb Sense Disambiguation Using Selectional Preferences Extracted with a State-of-the-art Semantic Role Labeler},\n type = {article},\n year = {2006},\n pages = {139-148},\n id = {99a46128-2ec2-3171-9d74-6678c75919db},\n created = {2012-04-01T16:32:49.000Z},\n file_attached = {false},\n profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},\n group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},\n last_modified = {2017-03-14T14:36:19.698Z},\n tags = {semantic role labeling},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Ye2006a},\n private_publication = {false},\n 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.},\n bibtype = {article},\n author = {Ye, Patrick and Baldwin, Timothy},\n journal = {Technology}\n}","author_short":["Ye, P.","Baldwin, T."],"bibbaseid":"ye-baldwin-verbsensedisambiguationusingselectionalpreferencesextractedwithastateoftheartsemanticrolelabeler-2006","role":"author","urls":{},"downloads":0,"html":""},"bibtype":"article","creationDate":"2020-02-06T23:48:12.138Z","downloads":0,"keywords":[],"search_terms":["verb","sense","disambiguation","using","selectional","preferences","extracted","state","art","semantic","role","labeler","ye","baldwin"],"title":"Verb Sense Disambiguation Using Selectional Preferences Extracted with a State-of-the-art Semantic Role Labeler","year":2006}