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Computational Consequences of Agreement and Ambiguity in Natural Language

dc.date.accessioned2004-10-04T15:14:41Z
dc.date.accessioned2018-11-24T10:14:37Z
dc.date.available2004-10-04T15:14:41Z
dc.date.available2018-11-24T10:14:37Z
dc.date.issued1988-11-01en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/6526
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/6526
dc.description.abstractThe 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?).en_US
dc.format.extent2889628 bytes
dc.format.extent1140647 bytes
dc.language.isoen_US
dc.titleComputational Consequences of Agreement and Ambiguity in Natural Languageen_US


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