The analysis of noun sequences using semantic information extracted from on-line dictionaries
The analysis of noun sequences using semantic information extracted from on-line dictionaries
MindNet: acquiring and structuring semantic information from text
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Structural patterns vs. string patterns for extracting semantic information from dictionaries
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Semantic analysis of Japanese noun phrases: a new approach to dictionary-based understanding
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Enhancing semantic digital library query using a content and service inference model (CSIM)
Information Processing and Management: an International Journal
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This paper describes a workbench system for constructing a dictionary to interpret compound nouns, which integrates the acquisition of semantic information and interpretation of compound nouns. First, we extract semantic information from a machine readable dictionary and corpora using regular expressions. Then, the semantic relation of compound nouns are interpreted based on semantic relations, semantic features extracted automatically, and subcategorization information according to the characteristics of a head noun, i.e. attributive or predicative. Experimental results show that our method using hybrid knowledge depending on the characteristics of a head noun improves the accuracy rate by 40.30% and the coverage rate by 12.73% better than previous researches using semantic relations extracted from MRDs. As compound nouns are highly productive and their interpretation requires hybrid knowledge, we propose a workbench for compound noun interpretation in which necessary knowledge such as semantic patterns, semantic relations, and interpretation instances can be extended, rather than assuming a pre-defined lexical knowledge.