William A. Gale

Also published as: William Gale


1996

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A Stochastic Finite-State Word-Segmentation Algorithm for Chinese
Richard W. Sproat | Chilin Shih | William Gale | Nancy Chang
Computational Linguistics, Volume 22, Number 3, September 1996

1995

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Inverse Document Frequency (IDF): A Measure of Deviations from Poisson
Kenneth Church | William Gale
Third Workshop on Very Large Corpora

1994

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A Stochastic Finite-State Word-Segmentation Algorithm for Chinese
Richard Sproat | Chilin Shih | William Gale | Nancy Chang
32nd Annual Meeting of the Association for Computational Linguistics

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Fax: An Alternative to SGML
Kenneth W. Church | William A. Gale | Jonathan I. Helfman | David D. Lewis
COLING 1994 Volume 1: The 15th International Conference on Computational Linguistics

1993

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A Program for Aligning Sentences in Bilingual Corpora
William A. Gale | Kenneth W. Church
Computational Linguistics, Volume 19, Number 1, March 1993, Special Issue on Using Large Corpora: I

1992

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Estimating Upper and Lower Bounds on the Performance of Word-Sense Disambiguation Programs
William Gale | Kenneth Ward Church | David Yarowsky
30th Annual Meeting of the Association for Computational Linguistics

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One Sense Per Discourse
William A. Gale | Kenneth W. Church | David Yarowsky
Speech and Natural Language: Proceedings of a Workshop Held at Harriman, New York, February 23-26, 1992

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Using bilingual materials to develop word sense disambiguation methods
William A. Gale | Kenneth W. Church | David Yarowsky
Proceedings of the Fourth Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages

1991

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A Program for Aligning Sentences in Bilingual Corpora
William A. Gale | Kenneth W. Church
29th Annual Meeting of the Association for Computational Linguistics

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Identifying Word Correspondences in Parallel Texts
William A. Gale | Kenneth W. Church
Speech and Natural Language: Proceedings of a Workshop Held at Pacific Grove, California, February 19-22, 1991

1990

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A Spelling Correction Program Based on a Noisy Channel Model
Mark D. Kemighan | Kenneth W. Church | William A. Gale
COLING 1990 Volume 2: Papers presented to the 13th International Conference on Computational Linguistics

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Poor Estimates of Context are Worse than None
William A. Gale | Kenneth W. Church
Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania, June 24-27,1990

1989

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Parsing, Word Associations and Typical Predicate-Argument Relations
Kenneth Church | William Gale | Patrick Hanks | Donald Hindle
Speech and Natural Language: Proceedings of a Workshop Held at Cape Cod, Massachusetts, October 15-18, 1989

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Enhanced Good-Turing and Cat-Cal: Two New Methods for Estimating Probabilities of English Bigrams (abbreviated version)
Kenneth W. Church | William A. Gale
Speech and Natural Language: Proceedings of a Workshop Held at Cape Cod, Massachusetts, October 15-18, 1989

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Parsing, Word Associations and Typical Predicate-Argument Relations
Kenneth Church | William Gale | Patrick Hanks | Donald Hindle
Proceedings of the First International Workshop on Parsing Technologies

There are a number of collocational constraints in natural languages that ought to play a more important role in natural language parsers. Thus, for example, it is hard for most parsers to take advantage of the fact that wine is typically drunk, produced, and sold, but (probably) not pruned. So too, it is hard for a parser to know which verbs go with which prepositions (e.g., set up) and which nouns fit together to form compound noun phrases (e.g., computer programmer). This paper will attempt to show that many of these types of concerns can be addressed with syntactic methods (symbol pushing), and need not require explicit semantic interpretation. We have found that it is possible to identify many of these interesting co-occurrence relations by computing simple summary statistics over millions of words of text. This paper will summarize a number of experiments carried out by various subsets of the authors over the last few years. The term collocation will be used quite broadly to include constraints on SVO (subject verb object) triples, phrasal verbs, compound noun phrases, and psychoiinguistic notions of word association (e.g., doctor/nurse).