연구 보고서 상세보기
Expanding Multi-dimensional Korean Dictionary based on Word Network
저자
Ok Cheol Young
연구책임자
Ok Cheol Young
펴낸 곳
The National Institute of The Korean Language
펴낸 때
2009
첨부파일 총 1건
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1. Objective of Research Project
• Addition of 10,000 nouns in polysemy level and construction of semantic relations(hypernym, hyponym, synomym, and antonym).
• Addition of 7,000 predicate in polysemy level and subcategorization mapped on Noun's Word Network.
• Part of Speech and polysemy tagging of definition and example sentences in Standard Korean Great Dictionary(STGD).
• Semantic clusterization of predicates.
• Design and implementation of browser for semantic clusters.
2. Necessities of Research Project
• In order to vitalize industry of Korean information, it is necessary to ensure machine readability of STGD.
• In order to grasp Korean lexical sematic information multidimensionaly and systematically, it is necessary to construct Korean dictionary based on lexical semantic system.
• Expanding continuously the Korean dictionary based on lexical semantic system constructed by the National Institute of the Korean Language (2008).
3. Content and Scope
• Selection of Additional words
- 50,328 words in polysemy level were selected in 2008 among 127,659 words extracted from 21th Sejong corpus and definitions in the STGD which were tagged in POS and polysemy level.
- Additional 10,000 nouns and 7,000 predicates are selected from the remained words in 2008 and the Sejong Electronic Dictionary on the criteria of words selection in 2008.
• Construction of semantic relations in polysemy level
- Construction of semantic relations(hypernym, hyponym, synomym, and antonym) for additional nouns.
- Modification of subcategories of predicates selected in 2008 and subcategorization for the additional predicates on the same criteria.
- Modification of semantic relation between adverbs and predicates.
• POS and polysemy tagging
- Definitions in STGD of the additional words.
- Examples in STGD of all selected definitions.
• Semantic clustering in polysemy level for all selected predicates.
• Design and implementation of WEB browser for semantic clusters.
4. Applications
• Extraction of various sematic information from POS and polysemy tagged definition and examples.
• Multi-dimensional grasp of various sematic relations (hypernym, hyponym, synomym, and antonym, subcategory, adverbs) using Web browser.