Automatic WordNet Mapping Using Word Sense Disambiguation

Automatic WordNet mapping using word sense disambiguation* Changki Lee Geunbae Leer Natural Language Processing Lab Dept. of Computer Science and Engineering Pohang University of Science & Technology San 31, Hyoja-Dong, Pohang, 790-784, Korea {leeck,gblee }@postech.ac.kr Seo JungYun Natural Language Processing Lab Dept. of Computer Science Sogang University Sinsu-dong 1, Mapo-gu, Seoul, Korea seojy@ ccs.sogang.ac.kr Abstract This paper presents the automatic construction of a Korean WordNet from pre-existing lexical resources. A set of automatic WSD techniques is described for linking Korean words collected from a bilingual MRD to English WordNet synsets. We will show how individual linking provided by each WSD method is then combined to produce a Korean WordNet for nouns. 1 Introduction There is no doubt on the increasing importance of using wide coverage ontologies for NLP tasks especially for information retrieval and cross-language information retrieval. While these ontologies exist in English, there are very few available wide range ontologies for other languages. Manual construction of the ontology by experts is the most reliable technique but is costly and highly time-consuming. This is the reason for many researchers having focused on massive acquisition of lexical knowledge and semantic information from pre-existing lexical resources as automatically as possible. This paper presents a novel approach for automatic WordNet mapping using word sense disambiguafion. The method has been applied to link Korean words from a bilingual dictionary to English WordNet synsets. To clarify the description, an example is given. To link the first sense of Korean word "gwan-mog" to WordNet synset, we employ a bilingual Korean-English dictionary. The first sense of 'gwan-mog' has 'bush' as a translation in English and 'bush' has five synsets in WordNet. Therefore the first sense of 'gwan-mog" has five candidate synsets. Somehow we decide a synset {shrub, bush} among five candidate synsets and link the sense of 'gwan-mog' to this synset. As seen from this example, when we link the senses of Korean words to WordNet synsets, there are semantic ambiguities. To remove the ambiguities we develop new word sense disambiguation heuristics and automatic mapping method to construct Korean WordNet based on the existing English WordNet. This paper is organized as follows. In section 2, we describe multiple heuristics for word sense disambiguation for sense linking. In section 3, we explain the method of combination for these heuristics. Section 4 presents some experiment results, and section 5 will discuss some related researches. Finally we draw some conclusions and future researches in section 6. The automatic mapping-based Korean WordNet plays a natural Korean-English bilingual thesaurus, so it will be directly applied to Korean-English cross-lingual information retrieval as well as Korean monolingual information retrieval. 2 Multiple heuristics for word sense disambiguation As the mapping method described in this paper has been developed for combining multiple individual solutions, each single heuristic must be seen as a container for some part of the linguistic knowledge needed to disarnbiguate the * This research was supported by KOSEF special purpose basic research (1997.9- 2000.8 #970-1020-301-3) Corresponding author 142 ambiguous WordNet synsets. Therefore, not …

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