Concordance

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We then use the <term> predicates </term> of	such	<term> clauses </term> to create a set of <term>	#5188 We then use the predicates of such clauses to create a set of domain independent features to annotate an input dataset, and run two different machine learning algorithms: SLIPPER, a rule-based learning algorithm, and TiMBL, a memory-based system.
the role of <term> user modeling </term> in	such	<term> systems </term> . It begins with a characterization	#16046 This paper explores the role of user modeling in such systems.
model </term> is also presented that deals	such	<term> phrases </term> , as well as a <term>	#7379 A statistical translation model is also presented that deals such phrases, as well as a training method based on the maximization of translation accuracy, as measured with the NIST evaluation metric.
word </term> blocks . In many cases though	such	movements still result in correct or almost	#10343 In many cases though such movements still result in correct or almost correct sentences.
of <term> parsing flexibilities </term> that	such	a system should provide . We go , on to	#12750 In this paper, we outline a set of parsing flexibilities that such a system should provide.
edges </term> adjacent to it , rather than all	such	<term> edges </term> as in conventional treatments	#17626 As each new edge is added to the chart, the algorithm checks only the topmost of the edges adjacent to it, rather than all such edges as in conventional treatments.
) <term> numeric-valued attributes </term> ,	such	as size or location ; ( b ) <term> perspective-taking	#10666 This paper discusses two problems that arise in the Generation of Referring Expressions: (a) numeric-valued attributes, such as size or location; (b) perspective-taking in reference.
</term> . We propose a method of attaining	such	a design through a method of <term> structure-sharing	#17984 We propose a method of attaining such a design through a method of structure-sharing which avoids log(d) overheads often associated with structure-sharing of graphs without any use of costly dependency pointers.
essential to provide an adequate explanation of	such	<term> discourse phenomena </term> as <term>	#14251 The distinction among these components is essential to provide an adequate explanation of such discourse phenomena as cue phrases, referring expressions, and interruptions.
languages with little <term> inflection </term>	such	as <term> English </term> , but fails for <term>	#16766 This approach is sufficient for languages with little inflectionsuch as English, but fails for highly inflective languages such as Czech, Russian, Slovak or other Slavonic languages.
building <term> spelling-checkers </term> for	such	languages . The speed of the resulting	#16804 We have developed a special method for describing inflection for the purpose of building spelling-checkers for such languages.
including <term> coordinate conjunctions </term>	such	as <term> and </term> , <term> or </term> , <term>	#19687 The authors propose a model for analyzing English sentences including coordinate conjunctionssuch as and, or, but and the equivalent words.
simulate many <term> grammar formalisms </term> ,	such	as <term> rewriting systems </term> , <term>	#11104 This formalism is both elementary and powerful enough to strongly simulate many grammar formalisms, such as rewriting systems, dependency grammars, TAG, HPSG and LFG.
Emotions </term> and other <term> indices </term>	such	as the <term> dominance distribution of speakers	#167 Emotions and other indicessuch as the dominance distribution of speakers might be available on the surface and could be used directly.
may offer additional <term> indices </term>	such	as the time and place of the rejoinder	#75 Traditional information retrieval techniques use a histogram of keywords as the document representation but oral communication may offer additional indicessuch as the time and place of the rejoinder and the attendance.
non-literal aspects of communication </term> ,	such	as robust <term> communication procedures	#12577 While such decoding is an essential underpinning, much recent work suggests that natural language interfaces will never appear cooperative or graceful unless they also incorporate numerous non-literal aspects of communication, such as robust communication procedures.
</term> , posing special problems for readers ,	such	as <term> misspelled words </term> , <term> missing	#13009 However, a great deal of natural language texts e.g., memos, rough drafts, conversation transcripts etc., have features that differ significantly from neat texts, posing special problems for readers, such as misspelled words, missing words, poor syntactic construction, missing periods, etc.
Finding the preferred <term> language </term> for	such	a <term> need </term> is a valuable task .	#10754 Finding the preferred language for such a need is a valuable task.
<term> highly inflective languages </term>	such	as <term> Czech </term> , <term> Russian </term>	#16776 This approach is sufficient for languages with little inflection such as English, but fails for highly inflective languagessuch as Czech, Russian, Slovak or other Slavonic languages.
speech </term> . Other contextual clues ,	such	as <term> editing terms </term> , <term> word	#21338 Other contextual clues, such as editing terms, word fragments, and word matchings, are also factored in by modifying the transition probabilities.


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