Bunt Harry, Nijholt Anton (auth.), Harry Bunt, Anton Nijholt's Advances in Probabilistic and Other Parsing Technologies PDF

By Bunt Harry, Nijholt Anton (auth.), Harry Bunt, Anton Nijholt (eds.)

ISBN-10: 9048155797

ISBN-13: 9789048155798

ISBN-10: 9401594708

ISBN-13: 9789401594707

Parsing know-how is worried with discovering syntactic constitution in language. In parsing we need to care for incomplete and never inevitably exact formal descriptions of ordinary languages. Robustness and potency are one of the major issuesin parsing. Corpora can be utilized to acquire frequency information regarding language use. this enables probabilistic parsing, an technique that goals at either robustness and potency elevate. Approximation strategies, to be utilized on the point of language description, parsing process, and syntactic illustration, have an analogous target. Approximation on the point of syntactic illustration is usually referred to as underspecification, a standard strategy to take care of syntactic ambiguity.
during this e-book new parsing applied sciences are accumulated that objective at attacking the issues of robustness and potency by means of precisely those ideas: the layout of probabilistic grammars and effective probabilistic parsing algorithms, approximation concepts utilized to grammars and parsers to extend parsing potency, and methods for underspecification and the mixing of semantic details within the syntactic research to house great ambiguity.
The e-book provides a cutting-edge evaluate of present examine and improvement in parsing applied sciences. In its chapters we see how probabilistic tools have entered the toolbox of computational linguistics so that it will be utilized in either parsing concept and parsing perform. The booklet is either a special reference for researchers and an advent to the sector for graduate students.

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Computational Linguistics, 19(4):591-636. Vijay-Shanker, K and Weir, D. (1994). The equivalence of four extensions of context-free grammars. Mathematical Systems Theory, 27:511-546. , and Joshi, A. (1987). Characterizing structural descriptions produced by various grammatical formalisms. In Proceedings of the 25th Meeting of the Association for Computational Linguistics, pp. 104-111. XTAG-Group, T. (1995). A lexicalized Tree Adjoining Grammar for English. Technical Report IRCS Report 95-03, The Institute for Research in Cognitive Science, University of Pennsylvania.

Joshi, A. and Srinivas, B. (1994). Disambiguation of super parts of speech (or supertags): almost parsing. In Proceedings of the 15th International Conference on Computational Linguistics, pp. 154-160. , and Temperley, D. (1992). Grammatical trigrams : a probabilistic model of Link Grammar. In AAAI Fall Symposium on Probabilistic Approaches to Natural Language, pp. 89-97. Magerman, D. (1995). Statistical decision-tree models for parsing . In Proceedings of the 33rd Meeting of the Association for Computational Linguistics, pp.

In contrast to SLG(2) - which is limited to giving the probability that a tree anchored with a given lexical item is substituted or adjoined into a tree anchored with a second lexical item - SLG(3) specifies the probability that a particular set of lexical items is combined in a derivation step. It is the elementary trees of the underlying LTAG that determine the (extended local) domains over which these dependencies can be expressed since it is the structure of an elementary tree that determines the possible daughters in a meta-production.

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Advances in Probabilistic and Other Parsing Technologies by Bunt Harry, Nijholt Anton (auth.), Harry Bunt, Anton Nijholt (eds.)


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