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	text browser </term> . We describe how this	information	is used in a <term> prototype system </term>	#317 We describe how this information is used in a prototype system designed to support information workers' access to a pharmaceutical news archive as part of their industry watch function.
other,30-4-P05-1074,bq	it can be refined to take <term> contextual	information	</term> into account . We evaluate our <term>	#9747 We define a paraphrase probability that allows paraphrases extracted from a bilingual parallel corpus to be ranked using translation probabilities, and show how it can be refined to take contextual information into account.
tech,13-2-P03-1030,bq	<term> new event detection </term> as <term>	information	retrieval task </term> and hypothesize on	#4076 In this paper we formulate story link detection and new event detection asinformation retrieval task and hypothesize on the impact of precision and recall on both systems.
tech,19-1-P03-1068,bq	large-scale <term> acquisition of word-semantic	information	</term> , e.g. the construction of <term> domain-independent	#4954 We describe the ongoing construction of a large, semantically annotated corpus resource as reliable basis for the large-scale acquisition of word-semantic information, e.g. the construction of domain-independent lexica.
	involves manual determination of whether an	information	nugget appears in a system 's response	#7561 Until now, the only way to assess the correctness of answers to such questions involves manual determination of whether an information nugget appears in a system's response.
	<term> theory </term> specifies how different	information	in <term> memory </term> affects the certainty	#11953 Unlike logic, the theory specifies how different information in memory affects the certainty of the conclusions drawn.
other,27-1-C04-1112,bq	maximum entropy ) </term> with <term> linguistic	information	</term> . Instead of building individual <term>	#6007 In this paper, we present a corpus-based supervised word sense disambiguation (WSD) system for Dutch which combines statistical classification (maximum entropy) with linguistic information.
	<term> inference types </term> , and how the	information	found in <term> memory </term> determines which	#12039 The paper also discusses how memory is structured in multiple ways to support the different inference types, and how the information found in memory determines which inference types are triggered.
other,1-3-I05-6011,bq	<term> referents </term> . This <term> referential	information	</term> is vital for resolving <term> zero	#8603 This referential information is vital for resolving zero pronouns and improving machine translation outputs.
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.
tech,6-1-N06-2038,bq	are several approaches that model <term>	information	extraction </term> as a <term> token classification	#10805 There are several approaches that modelinformation extraction as a token classification task, using various tagging strategies to combine multiple tokens.
	</term> puts different amounts and types of	information	into its <term> lexicon </term> according to	#15933 Although every natural language system needs a computational lexicon, each system puts different amounts and types of information into its lexicon according to its individual needs.
tech,1-4-N04-4028,bq	each <term> extracted field </term> . The <term>	information	extraction system </term> we evaluate is	#6812 Theinformation extraction system we evaluate is based on a linear-chain conditional random field (CRF), a probabilistic model which has performed well on information extraction tasks because of its ability to capture arbitrary, overlapping features of the input in a Markov model.
tech,1-4-H01-1001,bq	large database </term> . Traditional <term>	information	retrieval techniques </term> use a <term> histogram	#56 Traditionalinformation retrieval techniques use a histogram of keywords as the document representation but oral communication may offer additional indices such as the time and place of the rejoinder and the attendance.
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.
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,12-3-I05-5003,bq	</term> which leverages <term> part of speech	information	</term> of the <term> words </term> contributing	#8382 We also introduce a novel classification method based on PER which leverages part of speech information of the words contributing to the word matches and non-matches in the sentence.
other,12-3-N04-1022,bq	incorporate different levels of <term> linguistic	information	</term> from <term> word strings </term> , <term>	#6588 We describe a hierarchy of loss functions that incorporate different levels of linguistic information from word strings, word-to-word alignments from an MT system, and syntactic structure from parse-trees of source and target language sentences.
other,17-1-N06-2009,bq	to variations in the phrasing of an <term>	information	need </term> . Finding the preferred <term>	#10746 State-of-the-art Question Answering (QA) systems are very sensitive to variations in the phrasing of aninformation need.
	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.


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