Coping with syntactic ambiguity or how to put the block in the box on the table
Computational Linguistics
Canonical representation in NLP system design: a critical evaluation
ANLC '88 Proceedings of the second conference on Applied natural language processing
An efficient chart-based algorithm for partial-parsing of unrestricted texts
ANLC '92 Proceedings of the third conference on Applied natural language processing
A stochastic approach to sentence parsing
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
Control structures and theories of interaction in speech understanding systems
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
Predictive combinators: a method for efficient processing of combinatory Categorial Grammars
ACL '87 Proceedings of the 25th annual meeting on Association for Computational Linguistics
COLING '86 Proceedings of the 11th coference on Computational linguistics
Transformation of natural language into logical formulas
COLING '82 Proceedings of the 9th conference on Computational linguistics - Volume 1
A computational model of language performance: Data Oriented Parsing
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 3
A computational model of language performance: Data Oriented Parsing
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 3
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We will trace a brief history of context-free parsing algorithms and then describe some representation issues. The purpose of this paper is to share our philosophy and experience in adapting a well-known context free parsing algorithm (Earley''s algorithm and variations thereof) to the parsing of a difficult and wide ranging corpus of sentences. The sentences were gathered by Malhotra in an experiment which fooled businessmen users into thinking they were interacting with Malhotra in another room. The Malhotra corpus is considerably more difficult than a second collection published by the LADDER Group. Both collections are given in the appendices. Section 4 compares empirical results obtained from these collections against theoretical predictions.