Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
A logical semantics for feature structures
ACL '86 Proceedings of the 24th annual meeting on Association for Computational Linguistics
Two languages are more informative than one
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Automatic acquisition of subcategorization frames from untagged text
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Noun classification from predicate-argument structures
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Toward memory-based translation
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
Generalizing case frames using a thesaurus and the MDL principle
Computational Linguistics
Finding a domain-appropriate sense inventory for semantically tagging a corpus
Natural Language Engineering
ANLC '94 Proceedings of the fourth conference on Applied natural language processing
Structural matching of parallel texts
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Bilingual text, matching using bilingual dictionary and statistics
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Improvement in customizability using translation templates
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
A method for distinguishing exceptional and general examples in example-based transfer systems
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Two methods for learning ALT-J/E translation rules from examples and a semantic hierarchy
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Data driven approaches to speech and language processing
Nonlinear Speech Modeling and Applications
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For practical research in natural language processing, it is indispensable to develop a large scale semantic dictionary for computers. It is especially important to improve the techniques for compiling semantic dictionaries from natural language texts such as those in existing human dictionaries or in large corpora. However, there are at least two difficulties in analyzing existing texts: the problem of syntactic ambiguities and the problem of polysemy. Our approach to solve these difficulties is to make use of translation examples in two distinct languages that have quite different syntactic structures and word meanings. The reason we took this approach is that in many cases both syntactic and semantic ambiguities are resolved by comparing analyzed results from both languages. In this paper, we propose a method for resolving the syntactic ambiguities of translation examples of bilingual corpora and a method for acquiring lexical knowledge, such as case frames of verbs and attribute sets of nouns.