Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
Information-based syntax and semantics: Vol. 1: fundamentals
Information-based syntax and semantics: Vol. 1: fundamentals
Procedure for quantitatively comparing the syntactic coverage of English grammars
HLT '91 Proceedings of the workshop on Speech and Natural Language
Generating a grammar for statistical training
HLT '90 Proceedings of the workshop on Speech and Natural Language
Computational Linguistics - Special issue on inheritance: I
Inheritance in natural language processing
Computational Linguistics - Special issue on inheritance: I
A practical approach to multiple default inheritance for unification-based lexicons
Computational Linguistics - Special issue on inheritance: II
The acquisition and use of context-dependent grammars for English
Computational Linguistics
Theory of Syntactic Recognition for Natural Languages
Theory of Syntactic Recognition for Natural Languages
Generalized probabilistic LR parsing of natural language (Corpora) with unification-based grammars
Computational Linguistics - Special issue on using large corpora: I
Structural ambiguity and lexical relations
Computational Linguistics - Special issue on using large corpora: I
Coping with ambiguity and unknown words through probabilistic models
Computational Linguistics - Special issue on using large corpora: II
EACL '89 Proceedings of the fourth conference on European chapter of the Association for Computational Linguistics
Statistical decision-tree models for parsing
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Memory capacity and sentence processing
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Inside-outside reestimation from partially bracketed corpora
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
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This paper deals with the development of parsing techniques for the analysis of natural language sentences. We present a paradigm of a multi- path shift-reduce parser which combines two differently structured computational subsystems. The first uses information concerning native speakers' preferences, and the second deals with the linguistic knowledge. To apply preferences on parsing, we propose a method to rank the alternative partial analyses on the basis of parse context and frequency of use effects. The method is mainly based on psycholinguistic evidence, since we hope eventually to build a parser working as closely as possible to the way native speakers analyse natural sentences. We also discuss in detail techniques for optimizing the effectiveness of the proposed model. The system has worked successfully in parsing sentences in Modern Greek, a language where the relatively free word order characteristic results in many ambiguity problems. The proposed parsing model is consistent with many directions in the field of preference-based parsing, and it is proved to be adequate in building effective and maintainable natural language analysers. It is believed that this model can also be used in parsing sentences in languages other than Greek.