Learning Parse Decisions from Examples with Rich Context
نویسندگان
چکیده
We present a knowledge and context-based system for parsing natural language and evaluate it on sentences from the Wall Street Journal. Applying machine learning techniques, the system uses parse action examples acquired under supervision to generate a deterministic shift-reduce parser in the form of a decision structure. It relies heavily on context, as encoded in features which describe the morpholgical, syntactical, semantical and other aspects of a given parse state.
منابع مشابه
Learning Parse and Translation Decisions from Examples with Rich Context
We present a knowledge and context-based system for parsing and translating natural language and evaluate it on sentences from the Wall Street Journal. Applying machine learning techniques, the system uses parse action examples acquired under supervision to generate a deterministic shift-reduce parser in the form of a decision structure. It relies heavily on context, as encoded in features whic...
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متن کاملAppeared in Proceedings of the Association for Computational Linguistics ( ACL ) 1997 482
We present a knowledge and context-based system for parsing and translating natural language and evaluate it on sentences from the Wall Street Journal. Applying machine learning techniques, the system uses parse action examples acquired under supervision to generate a determinis-tic shift-reduce parser in the form of a decision structure. It relies heavily on context , as encoded in features wh...
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