Presentation 1996/10/11
Sense Discrimination of Verbs Using EDR Dictionary
Masaru HIGASHI, Tsunenori MINE, Makoto AMAMIYA,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Case frames are useful to discriminate verb senses. However, enough number of them required for analyzing general texts are not available. Therefore, it is important to develop a case frames acquiring method in the NLP field. Some case frames whose semantic features consist of a set of word concepts can be constructed from classifying lots of sentences by a verb sense. A key of classifying those sentences is a semantic distance (similarities) between the sentences. In this paper, we propose a method for constructing case frame that is based on similarities between words or sentences. The similarity is calculated using the EDR conceptual dictionary. We also reports. about experimental results for evaluating our method and features of EDR dictionaries.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Case Frame / Semantic Dictionary / Corpora / Similarity
Paper # NLC96-36
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Committee NLC
Conference Date 1996/10/11(1days)
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Paper Information
Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Sense Discrimination of Verbs Using EDR Dictionary
Sub Title (in English)
Keyword(1) Case Frame
Keyword(2) Semantic Dictionary
Keyword(3) Corpora
Keyword(4) Similarity
1st Author's Name Masaru HIGASHI
1st Author's Affiliation Dept. of Intelligent Systems, Graduate School of Information Science and Electrical Engineering, Kyushu University()
2nd Author's Name Tsunenori MINE
2nd Author's Affiliation Dept. of Intelligent Systems, Graduate School of Information Science and Electrical Engineering, Kyushu University
3rd Author's Name Makoto AMAMIYA
3rd Author's Affiliation Dept. of Intelligent Systems, Graduate School of Information Science and Electrical Engineering, Kyushu University
Date 1996/10/11
Paper # NLC96-36
Volume (vol) vol.96
Number (no) 294
Page pp.pp.-
#Pages 6
Date of Issue