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        <title>Probabilistic Methods in Dependency Grammar Parsing</title>
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            <title>Proceedings of the First International Workshop on Parsing Technologies</title>
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            <namePart type="given">Masaru</namePart>
            <namePart type="family">Tomita</namePart>
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            <publisher>Carnegy Mellon University</publisher>
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    <abstract>Authentic text as found in corpora cannot be described completely by a formal system, such as a set of grammar rules. As robust parsing is a prerequisite for any practical natural language processing system, there is certainly a need for techniques that go beyond merely formal approaches. Various possibilities, such as the use of simulated annealing, have been proposed recently and we have looked at their suitability for the parse process of the DLT machine translation system, which will use a large structured bilingual corpus as its main linguistic knowledge source. Our findings are that parsing is not the type of task that should be tackled solely through simulated annealing or similar stochastic optimization techniques but that a controlled application of probabilistic methods is essential for the performance of a corpus-based parser. On the basis of our explorative research we have planned a number of small-scale implementations in the near future.</abstract>
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        <date>1989-08</date>
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            <start>142</start>
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%0 Conference Proceedings
%T Probabilistic Methods in Dependency Grammar Parsing
%A van Zuijlen, Job M.
%Y Tomita, Masaru
%S Proceedings of the First International Workshop on Parsing Technologies
%D 1989
%8 August
%I Carnegy Mellon University
%C Pittsburgh, Pennsylvania, USA
%F van-zuijlen-1989-probabilistic
%X Authentic text as found in corpora cannot be described completely by a formal system, such as a set of grammar rules. As robust parsing is a prerequisite for any practical natural language processing system, there is certainly a need for techniques that go beyond merely formal approaches. Various possibilities, such as the use of simulated annealing, have been proposed recently and we have looked at their suitability for the parse process of the DLT machine translation system, which will use a large structured bilingual corpus as its main linguistic knowledge source. Our findings are that parsing is not the type of task that should be tackled solely through simulated annealing or similar stochastic optimization techniques but that a controlled application of probabilistic methods is essential for the performance of a corpus-based parser. On the basis of our explorative research we have planned a number of small-scale implementations in the near future.
%U https://aclanthology.org/W89-0215
%P 142-151

Markdown (Informal)

[Probabilistic Methods in Dependency Grammar Parsing](https://aclanthology.org/W89-0215) (van Zuijlen, IWPT 1989)

• Probabilistic Methods in Dependency Grammar Parsing (van Zuijlen, IWPT 1989)

ACL

• Job M. van Zuijlen. 1989. Probabilistic Methods in Dependency Grammar Parsing. In Proceedings of the First International Workshop on Parsing Technologies, pages 142–151, Pittsburgh, Pennsylvania, USA. Carnegy Mellon University.