Computational Consequences of Agreement and Ambiguity in Natural Language

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6526

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DC Field	Value	Language
dc.creator	Ristad, Eric Sven	-
dc.creator	Berwick, Robert C.	-
dc.date	2004-10-04T15:14:41Z	-
dc.date	2004-10-04T15:14:41Z	-
dc.date	1988-11-01	-
dc.date.accessioned	2013-10-09T02:45:54Z	-
dc.date.available	2013-10-09T02:45:54Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-1178	-
dc.identifier	http://hdl.handle.net/1721.1/6526	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	The computer science technique of computational complexity analysis can provide powerful insights into the algorithm-neutral analysis of information processing tasks. Here we show that a simple, theory-neutral linguistic model of syntactic agreement and ambiguity demonstrates that natural language parsing may be computationally intractable. Significantly, we show that it may be syntactic features rather than rules that can cause this difficulty. Informally, human languages and the computationally intractable Satisfiability (SAT) problem share two costly computional mechanisms: both enforce agreement among symbols across unbounded distances (Subject-Verb agreement) and both allow ambiguity (is a word a Noun or a Verb?).	-
dc.format	2889628 bytes	-
dc.format	1140647 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-1178	-
dc.title	Computational Consequences of Agreement and Ambiguity in Natural Language	-
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