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This paper proposes a method for automatically extracting term knowledge such as case relations and IS-A relations between words in the headline sentences of operating manuals for information equipments. The proposed method acquires term knowledge by the following iterative processing: the case relation extraction using correspondence relations between surface cases and deep cases; the case and IS-A relation extraction using compound word structures; the IS-A relation extraction using correspondence between the case structures in the hierarchical headline sentences. The distinctive feature of our method is to extract new case relations and IS-A relations by comparison and matching the case relations extracting from the super and sub headline sentences using the headline hierarchy. We have confirmed that the proposed method has achieved 92.4% recall and 96.8% precision for extracting case relations, and 93.9% recall and 89.9% precision for extracting IS-A relations from an operating manual of a car navigation system.

TERM KNOWLEDGE ACQUISITION USING THE STRUCTURE OF HEADLINE SENTENCESFROM INFORMATION EQUIPMENTS OPERATING MANUALS