Concordance

Query information 51 (2,377.7 per million)

	individual needs . However , some of the	information	needed across <term> systems </term> is shared	#15948 However, some of the information needed across systems is shared or identical information.
	<term> systems </term> is shared or identical	information	. This paper presents our experience in	#15956 However, some of the information needed across systems is shared or identical information.
other,20-3-C88-2166,bq	to be a repository of <term> shared lexical	information	</term> for use by <term> Natural Language	#15980 This paper presents our experience in planning and building COMPLEX, a computational lexicon designed to be a repository of shared lexical information for use by Natural Language Processing (NLP) systems.
	drawn primarily on explicit and implicit	information	from <term> machine-readable dictionaries	#16000 We have drawn primarily on explicit and implicit information from machine-readable dictionaries (MRD's) to create a broad coverage lexicon.
	is and how it can be used . The types of	information	that a <term> user model </term> may be required	#16070 The types of information that a user model may be required to keep about a user are then identified and discussed.
	tailored to the problem of extracting specific	information	from <term> unrestricted texts </term> where	#17565 We present an efficient algorithm for chart-based phrase structure parsing of natural language that is tailored to the problem of extracting specific information from unrestricted texts where many of the words are unknown and much of the text is irrelevant to the task.
	plausible interpretation from a chunk of	information	accumulated as the constraints . The interpretation	#18508 This makes it possible to express the vagueness of the spatial concepts and to derive the maximally plausible interpretation from a chunk of information accumulated as the constraints.
other,20-1-H92-1026,bq	takes advantage of detailed <term> linguistic	information	</term> to resolve <term> ambiguity </term> .	#18914 We describe a generative probabilistic model of natural language, which we call HBG, that takes advantage of detailed linguistic information to resolve ambiguity.
other,2-2-H92-1026,bq	, syntactic , semantic , and structural	information	</term> from the <term> parse tree </term> into	#18929 HBG incorporates lexical, syntactic, semantic, and structural information from the parse tree into the disambiguation process in a novel way.
tech,31-1-H92-1095,bq	recognition </term> , <term> knowledge-based	information	retrieval </term> and <term> image understanding	#19669 Language understanding work at Paramax focuses on applying general-purpose language understanding technology to spoken language understanding, text understanding, and document processing, integrating language understanding with speech recognition, knowledge-based information retrieval and image understanding.
other,12-5-A94-1007,bq	</term> , which provides <term> top-down scope	information	</term> of the correct <term> syntactic structure	#19798 This paper presents an English coordinate structure analysis model, which provides top-down scope information of the correct syntactic structure by taking advantage of the symmetric patterns of the parallelism.


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