TAILIEUCHUNG - Báo cáo khoa học: "Automatic Extraction of A spectual Information from a Monolingual Corpus"

This paper describes an approach to extract the aspectual information of Japanese verb phrases from a monolingual corpus. We classify Verbs into six categories by means of the aspectual features which are defined on the basis of the possibility of co-occurrence with aspectual forms and adverbs. A unique category could be identified for 96% of the target verbs. To evaluate the result of the experiment, we examined the meaning of -leiru which is one of the most fundamental aspectual markers in Japanese, and obtained the correct recognition score of 71% for the 200 sentences. . | Automatic Extraction of Aspectual Information from a Monolingual Corpus Akira Oishi Yuji Matsumoto Graduate School of Information Science Nara Institute of Science and Technology 8916-5 Takayama Ikoma Nara 630-01 Japan ryo-o matsu Abstract This paper describes an approach to extract the aspectual information of Japanese verb phrases from a monolingual corpus. We classify verbs into six categories by means of the aspectual features which are defined on the basis of the possibility of co-occurrence with aspectual forms and adverbs. A unique category could be identified for 96 of the target verbs. To evaluate the result of the experiment we examined the meaning of -teiru which is one of the most fundamental aspectual markers in Japanese and obtained the correct recognition score of 71 for the 200 sentences. 1 Introduction Aspect refers to the internal temporal structure of events and is distinguished from tense which has a deictic element in it. of reference to a point of time anchored by the speaker s utterance. There is a voluminous literature on aspect within linguistics and philosophy. Recently computational linguists also have joined in the act within the context of machine translation or text understanding etc. For example consider the following Japanese sentences quoted from Gunji 1992 . a . Ken-wa ima tonarino heya-de kimono-wo ki-te-i-ru. Ken-TOP now next room-LOC kimono-ACC put-on-PRES Ken is now putting on kimono in the next room. b . Ken-wa kesa-kara zutto ano kimono-wo ki-te-i-ru. Ken-TOP this morning-since always that kimono-ACC wear-PRES Ken has been wearing that kimono since this morning. c . Ken-wa ano kimono-wo san-nen maeni ki-te-i-ru. Ken-TOP that kimono-ACC three-year before wear-PRES Ken hits the experience of wearing that kimono three years ago. Notice that English translations use separate lexical items put on for a and wear for b c and different aspectual configurations the progressive for a the perfect progressive for b .

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• Monolingual Corpus
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• model language
• process natural language
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• Text mining
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• Interaction indicating term
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• Image processing
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• báo cáo hóa học
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• tài liệu về hóa học
• cách trình bày báo cáo
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• Features Extraction
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• Automatic Recognition
• healthcare professionals
• patients is essential
• evidence based
• official opinion
• Medicine availability
• private sector
• Genome Biology
• Gene expression data
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• Self organizing maps
• Semantic annotation
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• Knowledge base
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• Complex representation structure