Word Sense Disambiguation and Sense-Based NV Event Frame Identifier
Jia-Lin Tsai, Wen-Lian Hsu and Jeng-Woei Su
Word sense is ambiguous in natural language processing (NLP). This phenomenon is particularly keen in cases involving noun-verb (NV) word-pairs. This paper describes a sense-based noun-verb event frame (NVEF) identifier that can be used to disambiguate word sense in Chinese sentences effectively. A knowledge representation system (the NVEF-KR tree) for the NVEF sense-pair identifier is also proposed. We use the word sense of Hownet, which is a Chinese-English bilingual knowledge-base dictionary.
Our experiment showed that the NVEF identifier was able to achieve 74.8% accuracy for the test sentences studied based only on NVEF sense-pair knowledge. By applying the techniques of longest syllabic NVEF-word-pair first and exclusion word checking, the sense accuracy for the same test sentences could be further improved to 93.7%. There were four major reasons for the incorrect cases: (1) lack of a bottom-up tagger, (2) lack of non-NVEF knowledge, (3) inadequate word segmentation, and (4) lack of a multi-NVEF analyzer. If these four problems could be resolved, the accuracy would reach 98.9%.
The results of this study indicate that NVEF sense-pair knowledge is effective for word sense disambiguation and is likely to be important for general NLP.
word sense disambiguation, event frame, top-down identifier, Hownet
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