Ezra Black, Fred Jelinek, John Lafferty, David M. Magerman, Robert Mercer, Salim Roukos  Home/Search
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Abstract: We describe a generarive probabilistic model of natural language, which we call HBG, that takes advantage of detailed linguistic information to resolve ambiguity. HBG incorporates lexical, syntactic, semantic, and structural information from the parse tree into the disambiguation process in a novel way. We use a corpus of bracketed sentences, called a Treebank, in combination with decision tree building to tease out the relevant aspects of a parse tree that will determine the correct parse of a ... (Update)
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BibTeX entry: (Update)
Black, E.; Jelineck, F.; Lafferty, J.; Magerman, D.; Mercer, R.; and Roukos, S. 1993. Towards historybased grammars: Using richer models for probabilistic parsing. In Proceedings of the 31st Annual Meeting of the Association for Computational Linguistics, 31--37. http://citeseer.ist.psu.edu/black93towards.html More
@inproceedings{ black93towards,
author = "Ezra Black and Frederick Jelinek and John D. Lafferty and David M. Magerman and Robert L. Mercer and Salim Roukos",
title = "Towards History-Based Grammars: Using Richer Models for Probabilistic Parsing",
booktitle = "Meeting of the Association for Computational Linguistics",
pages = "31-37",
year = "1993",
url = "citeseer.ist.psu.edu/black93towards.html" }
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