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Parallel processing of natural language

Thesis/Dissertation ·
OSTI ID:7011627
Two types of parallel natural language processing are studied in this work: (1) the parallelism between syntactic and nonsyntactic processing and (2) the parallelism within syntactic processing. It is recognized that a syntactic category can potentially be attached to more than one node in the syntactic tree of a sentence. Even if all the attachments are syntactically well-formed, nonsyntactic factors such as semantic and pragmatic consideration may require one particular attachment. Syntactic processing must synchronize and communicate with nonsyntactic processing. Two syntactic processing algorithms are proposed for use in a parallel environment: Early's algorithm and the LR(k) algorithm. Conditions are identified to detect the syntactic ambiguity and the algorithms are augmented accordingly. It is shown that by using nonsyntactic information during syntactic processing, backtracking can be reduced, and the performance of the syntactic processor is improved. For the second type of parallelism, it is recognized that one portion of a grammar can be isolated from the rest of the grammar and be processed by a separate processor. A partial grammar of a larger grammar is defined. Parallel syntactic processing is achieved by using two processors concurrently: the main processor (mp) and the two processors concurrently: the main processor (mp) and the auxiliary processor (ap).
Research Organization:
Northwestern Univ., Evanston, IL (USA)
OSTI ID:
7011627
Country of Publication:
United States
Language:
English

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Related Subjects

99 GENERAL AND MISCELLANEOUS
990210* -- Supercomputers-- (1987-1989)
ALGORITHMS
COMPUTERS
CORRECTIONS
DIGITAL COMPUTERS
FAULT TOLERANT COMPUTERS
MATHEMATICAL LOGIC
NATURAL LANGUAGE
PARALLEL PROCESSING
PERFORMANCE
PROGRAMMING
PROGRAMMING LANGUAGES