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1
Articles - The Need for Accurate Alignment in Natural Language System Evaluation
In: Computational linguistics. - Cambridge, Mass. : MIT Press 27 (2001) 2, 231-248
OLC Linguistik
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2
The need for accurate alignment in natural language system evaluation
In: Computational linguistics. - Cambridge, Mass. : MIT Press 27 (2001) 2, 231-248
BLLDB
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3
Using Information Extraction to Improve Document Retrieval
In: DTIC (1998)
BASE
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4
Finite state language processing
Roche, Emmanuel (Hrsg.); Silberztein, Max (Mitarb.); Laporte, Eric (Mitarb.). - Cambridge, Mass. [u.a.] : MIT Press, 1997
BLLDB
UB Frankfurt Linguistik
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5
FASTUS: A Cascaded Finite-State Transducer for Extracting Information from Natural-Language Text ...
BASE
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6
SRI International FASTUS System MUC-6 Test Results and Analysis
In: DTIC (1995)
BASE
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7
Topics, methods and formalisms in syntax, semantics and pragmatics
Joshi, Aravind K. (Mitarb.); Hobbs, Jerry R. (Mitarb.); Bear, John (Mitarb.)...
In: Linguistica computazionale. - Pisa : Giardini 9-10 (1994), 489-595
BLLDB
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8
A System for Labeling Self-Repairs in Speech
In: DTIC (1993)
BASE
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9
SRI International Fastus System MUC-4 Test Results and Analysis
In: DTIC (1992)
BASE
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10
Detection and Correction of Repairs in Human-Computer Dialog
In: DTIC (1992)
BASE
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11
SRI International: Description of the FASTUS System Used for MUC-4
In: DTIC (1992)
BASE
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12
FASTUS: A System for Extracting Information from Natural-Language Text
In: DTIC AND NTIS (1992)
Abstract: FASTUS is a system for extracting information from free text in English, and potentially other languages as well, for entry into a database, and potentially for other applications. It works essentially as a cascaded, nondeterministic finite state automaton. There are four steps in the operation of FASTUS. In Step (1) sentences are scanned for certain trigger words to determine whether further processing should be done. In Step (2) noun groups, verb groups, and prepositions and some other particles are recognized. The input to Step (3) is the sequence of phrases recognized in Step (2); patterns of interest are identified in Step (3) and corresponding incident structures are built up. In Step (4) incident structures that derive from the same incident are identified and merged, and these are used in generating database entries. FASTUS is an order of magnitude faster than any comparable system; it can process a news report in an average of less than eleven seconds. This translates directly into fast development time. In the three and a half weeks between its first use and the MUC-4 evaluation in May 1992, we were able to build up its domain knowledge to a point where it was among the leaders in the evaluation.
Keyword: *ARTIFICIAL INTELLIGENCE; *INFORMATION RETRIEVAL; *NATURAL LANGUAGE; Cybernetics; DATA BASES; FASTUS TEXT PROCESSING; FASTUS(FINITE STATE AUTOMATION TEXT UNDERSTANDING SYSTEM); Information Science; INPUT; PATTERNS; PROCESSING; SEQUENCES
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA259435
http://www.dtic.mil/docs/citations/ADA259435
BASE
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13
The TACITUS System: The MUC-3 Experience
In: DTIC (1991)
BASE
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14
Robust Processing of Real-World Natural-Language Texts
In: DTIC AND NTIS (1991)
BASE
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15
Two principles of parse preference
In: COLING-90. Vol. 3. - Helsinki : Univ. of Helsinki (1990), 162-167
BLLDB
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16
Backwards phonology
In: COLING-90. Vol. 3. - Helsinki : Univ. of Helsinki (1990), 13-20
BLLDB
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17
Prosody, syntax and parsing
In: Association for Computational Linguistics. Proceedings of the conference. - Stroudsburg, Penn. : ACL 28 (1990), 17-22
BLLDB
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18
Two Principles of Parse Preference
In: DTIC (1990)
BASE
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19
Prosody, Syntax and Parsing
In: DTIC (1990)
BASE
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20
Morphology with Two-Level Rules and Negative Rule Features
In: DTIC (1989)
BASE
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