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Hits 21 – 40 of 58

21
Coping with ambiguity and unknown words through probabilistic models
In: Using large corpora. - Cambridge, Mass. [u.a.] : MIT Press (1994), 319-342
BLLDB
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22
Coping with Ambiguity and Unknown Words through Probabilistic Models
In: Computational linguistics. - Cambridge, Mass. : MIT Press 19 (1993) 2, 359-382
OLC Linguistik
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23
Using large corpora: II
Biber, Douglas (Mitarb.); Brent, Michael R. (Mitarb.); Brown, Peter F. (Mitarb.)...
In: Computational linguistics. - Cambridge, Mass. : MIT Press 19 (1993) 2, 219-382
BLLDB
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24
The future of computational linguistics
In: Challenges in natural language processing (Cambridge [etc.], 1993), p. 283-288
MPI für Psycholinguistik
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25
Critical challenges for natural language processing
In: Challenges in natural language processing (Cambridge [etc.], 1993), p. 3-36
MPI für Psycholinguistik
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26
Challenges in natural language processing
Bates, Madeleine; Weischedel, Ralph M.. - Cambridge [etc.] : Cambridge University Press, 1993
MPI für Psycholinguistik
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27
Challenges in natural language processing
Bates, Madeleine (Hrsg.); Weischedel, Ralph M. (Hrsg.). - Cambridge [u.a.] : Cambridge Univ. Press, 1993
BLLDB
UB Frankfurt Linguistik
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28
The future of computational linguistics
In: Challenges in natural language processing. - Cambridge [u.a.] : Cambridge Univ. Press (1993), 283-288
BLLDB
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29
Critical challenges for natural language processing
In: Challenges in natural language processing. - Cambridge [u.a.] : Cambridge Univ. Press (1993), 3-34
BLLDB
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30
Coping with Ambiguity and Unknown Words through Probabilistic Models
In: DTIC (1993)
Abstract: From spring 1990 through fall 1991, we performed a battery of small experiments to test the effectiveness of supplementing knowledge-based techniques with probabilistic models. This paper reports our experiments in predicting parts of speech of highly ambiguous words, predicting the intended interpretation of an utterance when more than one interpretation satisfies all known syntactic and semantic constraints, and learning case frame information for verbs from example uses. From these experiments, we are convinced that probabilistic models based on annotated corpora can effectively reduce the ambiguity in processing text and can be used to acquire lexical information from a corpus, by supplementing knowledge-based techniques. Based on the results of those experiments, we have constructed a new natural language system (PLUM)for extracting data from text, e.g., newswire text. ; Published in Computational Linguistics, v19 n2 p359-382, June 1993.
Keyword: *WORDS(LANGUAGE); AMBIGUITY; LEARNING; Linguistics; PROBABILITY; SEMANTICS; SYNTAX
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA574703
http://www.dtic.mil/docs/citations/ADA574703
BASE
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31
BBN: Description of the PLUM System as Used for MUC-5
In: DTIC (1993)
BASE
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32
BBN's PLUM Probabilistic Language Understanding System
In: DTIC (1993)
BASE
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33
A New Approach to Text Understanding
In: DTIC (1992)
BASE
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34
BBN: Description of the PLUM System as Used for MUC-4
In: DTIC (1992)
BASE
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35
BBN PLUM: MUC-4 Test Results and Analysis
In: DTIC (1992)
BASE
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36
BBN PLUM: MUC-3 Test Results and Analysis
In: DTIC (1991)
BASE
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37
BBN: Description of the PLUM System as Used for MUC-3
In: DTIC (1991)
BASE
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38
Multiple underlying systems : translating user requests into programs to produce answers
In: Association for Computational Linguistics. Proceedings of the conference. - Stroudsburg, Penn. : ACL 28 (1990), 227-234
BLLDB
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39
Portability in the Janus Natural Language Interface
In: DTIC (1989)
BASE
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40
Research and Development in Natural Language Understanding as Part of the Strategic Computing Program
In: DTIC AND NTIS (1989)
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