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We follow our previous work ( Dickinson et al. , 2010 ) in our feature choices , using a fiveword window that includes the target stem and two words on either side for context ( see also Tetreault and Chodorow , 2008 ) .
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Adjectives , more than other categories , are a striking example of regular polysemy since they are able to take on different meanings depending on their context , viz. , the noun or noun class they modify ( see Pustejovsky ( 1995 ) and the references therein ) .
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According to Dalrymple ( 2001 ) , LFG assumes the following universally available inventory of grammatical functions : SUBJ ( ect ) , OBJ ( ect ) , OBJe , COMP , XCOMP , OBL ( ique ) e , ADJ ( unct ) , XADJ .
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But their importance has grown far beyond machine translation : for instance , transferring annotations between languages ( Yarowsky and Ngai 2001 ; Hwa et al. 2005 ; Ganchev , Gillenwater , and Taskar 2009 ) ; discovery of paraphrases ( Bannard and Callison-Burch 2005 ) ; and joint unsupervised POS and parser induction across languages ( Snyder and Barzilay 2008 ) .
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4 This interpretation of the signature is sometimes referred to as closed world ( Gerdemann and King 1994 ; Gerdemann 1995 ) .
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Our training examples are similar to the data created for pseudodisambiguation , the usual evaluation task for SP models ( Erk , 2007 ; Keller and Lapata , 2003 ; Rooth et al. , 1999 ) .
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There have already been several attempts to develop distributed NLP systems for dialogue systems ( Bayer et al. , 2001 ) and speech recognition ( Hacioglu and Pellom , 2003 ) .
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For instance , implementing an efficient version of the MXPOST POS tagger ( Ratnaparkhi , 1996 ) will simply involve composing and configuring the appropriate text file reading component , with the sequential tagging component , the collection of feature extraction components and the maximum entropy model component .
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cue word and name the first ( or several ) associated words that come to mind ( e.g. , Nelson et al. ( 2004 ) ) , and feature norms , where subjects are given a cue word and asked to describe typical properties of the cue concept ( e.g. , McRae et al. ( 2005 ) ) .
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Hirschberg and Litman ( 1987 ) and Litman and Hirschberg ( 1990 ) also examine the relation between discourse and prosodic phrasing .
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Sarkar and Zeman ( 2000 ) evaluate 914 Czech verbs against a custom-made gold standard and record a token recall of 88 % .
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We use two measures from Information Retrieval to determine the quality of an automatically generated response : precision and F-score ( van Rijsbergen 1979 ; Salton and McGill 1983 ) .
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The automation of help-desk responses has been previously tackled using mainly knowledge-intensive paradigms , such as expert systems ( Barr and Tessler 1995 ) and case-based reasoning ( Watson 1997 ) .
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Xue and Palmer ( 2004 ) did very encouraging work on the feature calibration of semantic role labeling .
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This approach , which uses words that appear in the context of terms to formulate hypotheses on their semantic relatedness ( Habert et al. , 1996 , for example ) , does not specify the relationship itself .
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And ( Glickman and Dagan , 2003 ) use clustering and similarity measures to identify similar contexts in a single corpus and extract verbal paraphrases from these contexts .
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Not having to represent the frame explicitly not only enables the linguist to express only the relevant things , but also allows a more compact representation of lexical rules where explicit framing would require the rules to be split up ( Meurers 1994 ) .
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There has also been work focused upon determining the political leaning ( e.g. , `` liberal '' vs. `` conservative '' ) of a document or author , where most previously-proposed methods make no direct use of relationships between the documents to be classified ( the `` unlabeled '' texts ) ( Laver et al. , 2003 ; Efron , 2004 ; Mullen and Malouf , 2006 ) .
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Other similar approaches include those of Cicekli and G ¨ uvenir ( 1996 ) , McTait and Trujillo ( 1999 ) , Carl ( 1999 ) , and Brown ( 2000 ) , inter alia .
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To sum up , this work has been carried out to automatically classify Arabic documents using the NB algorithm , with the use of a different data set , a different number of categories , and a different root extraction algorithm from those used in ( Yahyaoui , 2001 ) .
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Our work builds on earlier research on learning to identify dialogues in which the user experienced poor speech recognizer performance ( Litman et al. , 1999 ) .
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CCGBank ( Hockenmaier and Steedman 2007 ) is used to train the model .
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More recent work on terminology structuring has focussed on formal similarity to develop hypotheses on the semantic relationships between terms : Daille ( 2003 ) uses derivational morphology ; Grabar and Zweigenbaum ( 2002 ) use , as a starting point , a number of identical characters .
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Some researchers ( Cucerzan , 2007 ; Nguyen and Cao , 2008 ) have explored the use of Wikipedia information to improve the disambiguation process .
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To address this issue , we use a version of the PATB3 training and dev sets manually annotated with functional gender , number , and rationality ( Alkuhlani and Habash 2011 ) .18 This is the first resource providing all three features ( ElixirFm only provides functional number , and to some extent functional gender ) .
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One approach to this problem is that taken by the ASCOT project ( Akkerman et al. , 1985 ; Akkerman , 1986 ) .
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Narrative writings or essays are creative works and they generally treat ownership as authorship , even for the most enthusiastic fellows of free culture ( Stallman , 2001 ) .
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McDonald has even argued for extending the model to a large number of components ( McDonald 1988 ) , and several systems have indeed added an additional component between the planner and the linguistic component ( Meteer 1994 ; Panaget 1994 ; Wanner 1994 ) .
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According to current tagger comparisons ( van Halteren et al. , 1998 ; Zavrel and Daelemans , 1999 ) , and according to a comparsion of the results presented here with those in ( Ratnaparkhi , 1996 ) , the Maximum Entropy framework seems to be the only other approach yielding comparable results to the one presented here .
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Similar findings have been proposed by Pandharipande ( 1993 ) that points out V1 and V2 are paired on the basis of their semantic compatibility , which is subject to syntactic constraints .
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The first lexical substitution method was proposed by Chapman and Davida ( 1997 ) .
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This can be a hazardous affair , since vague expressions tend to be interpreted in different ways by different people ( Toogood 1980 ) , sometimes in stark contrast with the intention of the speaker/writer ( Berry , Knapp , and Raynor 2002 ) .
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We see no good reason , however , why such text spans should necessarily be sentences , since the majority of tagging paradigms ( e.g. , Hidden Markov Model [ HMM ] [ Kupiec 1992 ] , Brill 's [ Brill 1995a ] , and MaxEnt [ Ratnaparkhi 1996 ] ) do not attempt to parse an entire sentence and operate only in the local window of two to three tokens .
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Hermann and Deutsch ( 1976 ; also reported in Levelt 1989 ) show that greater differences are most likely to be chosen , presumably because they are more striking .
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Nevertheless , recent results show that knowledge-poor methods perform with amazing accuracy ( cfXXX ( Mitkov , 1998 ) , ( Kennedy and Boguraev , 1996 ) ( Kameyama , 1997 ) ) .
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Notice that it is not possible to use corpus annotation to determine the likelihood of a given property to be chosen , unless we know in advance all of the properties that can be attributed to a given object , as in the case of Jordan 's work on the COCONUT domain ( Jordan , 2000 ) .
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Some well-known approaches include rule-based models ( Brill and Resnik 1994 ) , backed-off models ( Collins and Brooks 1995 ) , and a maximumentropy model ( Ratnaparkhi 1998 ) .
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Other psycholing-uistic studies that confirm the validity of paragraph units can be found in Black and Bower ( 1979 ) and Haberlandt et al. ( 1980 ) .
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Tetreault 's contribution features comparative evaluation involving the author 's own centering-based pronoun resolution algorithm called the Left-Right Centering algorithm ( LRC ) as well as three other pronoun resolution methods : Hobbs 's naive algorithm ( Hobbs 1978 ) , BFP ( Brennan , Friedman , and Pollard 1987 ) , and Strube 's 5list approach ( Strube 1998 ) .
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Lapalme and Kosseim ( 2003 ) investigated three approaches to the automatic generation of response e-mails : text classification , case-based reasoning , and question answering .
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This contrasts with one of the traditional approaches ( e.g. , Dorr 1994 ; Watanabe 1995 ) to posing the translation problem , i.e. , the approach in which translation problems are seen in terms of bridging the gap between the most natural monolingual representations underlying the sentences of each language .
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In practical context , German , English , and Japanese HPSG-based grammars are developed and used in the Verbmobil project ( Kay et al. , 1994 ) .
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Thus , over the past few years , along with advances in the use of learning and statistical methods for acquisition of full parsers ( Collins , 1997 ; Charniak , 1997a ; Charniak , 1997b ; Ratnaparkhi , 1997 ) , significant progress has been made on the use of statistical learning methods to recognize shallow parsing patterns syntactic phrases or words that participate in a syntactic relationship ( Church , 1988 ; Ramshaw and Marcus , 1995 ; Argamon et al. , 1998 ; Cardie and Pierce , 1998 ; Munoz et al. , 1999 ; Punyakanok and Roth , 2001 ; Buchholz et al. , 1999 ; Tjong Kim Sang and Buchholz , 2000 ) .
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For example , such schema can serve as a mean to represent translation examples , or find structural correspondences for the purpose of transfer grammar learning ( Menezes & Richardson , 2001 ) , ( Aramaki et al. , 2001 ) , ( Watanabe et al. , 2000 ) , ( Meyers et al. , 2000 ) , ( Matsumoto et al. , 1993 ) , ( kaji et al. , 1992 ) , and example-base machine translation EBMT3 ( Sato & Nagao , 1990 ) , ( Sato , 1991 ) , ( Richardson et al. , 2001 ) , ( Al-Adhaileh & Tang , 1999 ) .
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While IA is generally thought to be consistent with findings on human language production ( Hermann and Deutsch 1976 ; Levelt 1989 ; Pechmann 1989 ; Sonnenschein 1982 ) , the hypothesis that incrementality is a good model of human GRE seems unfalsifiable until a preference order is specified for the properties on which it operates .
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It helps them build complex knowledge bases by combining components : events , entities and modifiers ( Clark and Porter , 1997 ) .
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Our group has developed a wide-coverage HPSG grammar for Japanese ( Mitsuishi et al. , 1998 ) , which is used in a high-accuracy Japanese dependency analyzer ( Kanayama et al. , 2000 ) .
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Word frequency counts in internet search engines are inconsistent and unreliable ( Veronis , 2005 ) .
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Other milestones of recent research include the deployment of probabilistic and machine learning techniques ( Aone and Bennett 1995 ; Kehler 1997 ; Ge , Hale , and Charniak 1998 ; Cardie and Wagstaff 1999 ; the continuing interest in centering , used either in original or in revised form ( Abracos and Lopes 1994 ; Strube and Hahn 1996 ; Hahn and Strube 1997 ; Tetreault 1999 ) ; and proposals related to the evaluation methodology in anaphora resolution ( Mitkov 1998a , 2001b ) .
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It is only recently that the web name ambiguity has been approached as a separate problem and defined as an NLP task Web People Search on its own ( Artiles et al. , 2005 ; Artiles et al. , 2007 ) .
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Actually , if we use LSH technique ( Andoni and Indyk , 2008 ) in retrieval process , the local method can be easily scaled to a larger training data .
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Many lexicons , both automatically acquired and manually created , are more fine grained in their approaches to subcategorized clausal arguments , differentiating , for example , between a that-clause and a to + infinitive clause ( Ushioda et al. 1993 ) .
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Others provide automatic mappings of natural language instructions to executable actions , such as interpreting navigation directions ( Chen and Mooney , 2011 ) or robot commands ( Tellex et al. , 2011 ; Matuszek et al. , 2012 ) .
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Agreement between two annotation sets is calculated here in terms of Cohen 's kappa ( Cohen , 1960 ) 1 and corrected kappa ( Brennan and Prediger , 1981 ) 2 .
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Second , software for utilizing this ontology already exists : MetaMap ( Aronson 2001 ) identifies concepts in free text , and SemRep ( Rindflesch and Fiszman 2003 ) extracts relations between the concepts .
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The implementation has been inspired by experience in extracting information from very large corpora ( Curran and Moens , 2002 ) and performing experiments on maximum entropy sequence tagging ( Curran and Clark , 2003 ; Clark et al. , 2003 ) .
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Some efforts have tackled tasks such as automatic image caption generation ( Feng and Lapata , 2010a ; Ordonez et al. , 2011 ) , text illustration ( Joshi et al. , 2006 ) , or automatic location identification of Twitter users ( Eisenstein et al. , 2010 ; Wing and Baldridge , 2011 ; Roller et al. , 2012 ) .
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These types of features result in an improvement in both the mention detection and coreference resolution performance , as shown through experiments on the ACE 2004 Arabic data .
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The use of the web as a corpus for teaching and research on language has been proposed a number of times ( Kilgarriff , 2001 ; Robb , 2003 ; Rundell , 2000 ; Fletcher , 2001 , 2004b ) and received a special issue of the journal Computational Linguistics ( Kilgarriff and Grefenstette , 2003 ) .
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But while Bod 's estimator obtains state-of-the-art results on the WSJ , comparable to Charniak ( 2000 ) and Collins ( 2000 ) , Bonnema et al. 's estimator performs worse and is comparable to Collins ( 1996 ) .
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The implementation has been inspired by experience in extracting information from very large corpora ( Curran and Moens , 2002 ) and performing experiments on maximum entropy sequence tagging ( Curran and Clark , 2003 ; Clark et al. , 2003 ) .
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Another line of research approaches grounded language knowledge by augmenting distributional approaches of word meaning with perceptual information ( Andrews et al. , 2009 ; Steyvers , 2010 ; Feng and Lapata , 2010b ; Bruni et al. , 2011 ; Silberer and Lapata , 2012 ; Johns and Jones , 2012 ; Bruni et al. , 2012a ; Bruni et al. , 2012b ; Silberer et al. , 2013 ) .
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14We parse each sentence with the Collins parser ( Collins , 1999 ) .
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Encouraged by the success of chunk-based verb reordering lattices on ArabicEnglish ( Bisazza and Federico , 2010 ) , we tried to adapt the same approach to the German-English language pair .
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We followed the same experimental procedure as discussed in ( Taft , 2004 ) for English polymorphemic words .
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In our experiments , we employed the well-known classifier SVM `` ght to obtain individual-document classification scores , treating Y as the positive class and using plain unigrams as features .5 Following standard practice in sentiment analysis ( Pang et al. , 2002 ) , the input to SVM `` ght consisted of normalized presence-of-feature ( rather than frequency-of-feature ) vectors .
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The problem of handling ill-formed input has been studied by Carbonell and Hayes ( 1983 ) , Granger ( 1983 ) , Jensen et al. ( 1983 ) , Kwasny and Sondheimer ( 1981 ) , Riesbeck and Schank ( 1976 ) , Thompson ( 1980 ) , Weischedel and Black ( 1980 ) , and Weischedel and Sondheimer ( 1983 ) .
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To address this problem , we are currently working on developing a metagrammar in the sense of ( Candito , 1999 ) .
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Sentences like 12 , from Chomsky ( 1965 ) , are frequently cited .
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After the PropBank ( Xue and Palmer 2003 ) was built , Xue and Palmer ( 2005 ) and Xue ( 2008 ) have produced more complete and systematic research on Chinese SRL .
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In order to estimate the parameters of our model , we develop a blocked sampler based on that of Johnson et al. ( 2007 ) to sample parse trees for sentences in the raw training corpus according to their posterior probabilities .
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The extraction procedure utilizes a head percolation table as introduced by Magerman ( 1995 ) in combination with a variation of Collins 's ( 1997 ) approach to the differentiation between complement and adjunct .
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Many other such cases are described in Danlos 's book ( Danlos 1987 ) .
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• Before indexing the text , we process it with Textract ( Byrd and Ravin , 1998 ; Wacholder et al. , 1997 ) , which performs lemmatization , and discovers proper names and technical terms .
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Therefore , we repeated the experiments with POS tags predicted by the MADA toolkit ( Habash and Rambow 2005 ; Habash , Rambow , and Roth 2012 ) 15 ( see Table 2 , 14 Some parsers predict POS tags internally , instead of receiving them as input , but this is not the case in this article .
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Experiments on Chinese SRL ( Xue and Palmer 2005 , Xue 2008 ) reassured these findings .
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An example of this is the estimation of maximum entropy models , from simple iterative estimation algorithms used by Ratnaparkhi ( 1998 ) that converge very slowly , to complex techniques from the optimisation literature that converge much more rapidly ( Malouf , 2002 ) .
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According to Budanitsky and Hirst ( 2006 ) , there are three prevalent approaches for evaluating SR measures : mathematical analysis , applicationspecific evaluation and comparison with human judgments .
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The choice of learning algorithm for each classifier is motivated by earlier findings showing that discriminative classifiers outperform other machine-learning methods on error correction tasks ( Rozovskaya and Roth , 2011 ) .
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A good study comparing document categorization algorithms can be found in ( Yang and Liu , 1999 ) .
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For HMMs ( footnote 11 ) , Ti is the familiar trellis , and we would like this computation of ti to reduce to the forwardbackward algorithm ( Baum , 1972 ) .
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We follow Stymne and Cancedda ( 2011 ) , for compound merging .
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Semantic filters can also be used to prevent multiple versions of the same case frame ( Fillmore 1968 ) showing up as complements .
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The terms have been identified as the most specific to our corpus by a program developed by Drouin ( 2003 ) and called TER1vloSTAT .
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For statistical significance , we use McNemar 's test on non-gold LAS , as implemented by Nilsson and Nivre ( 2008 ) .
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The availability of toolkits for this weighted case ( Mohri et al. , 1998 ; van Noord and Gerdemann , 2001 ) promises to unify much of statistical NLP .
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tionally reconstructed by Alshawi and Crouch ( 1992 ) and Crouch and Putman ( 1994 ) , the context-independent meaning of a sentence is given by one or more QLFs that are built directly from syntactic and semantic rules .
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We use a standard split of 268 training documents , 68 development documents , and 106 testing documents ( Culotta et al. , 2007 ; Bengtson and Roth , 2008 ) .
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Bojar and Kos ( 2010 ) improved on this by marking prepositions with the case they mark ( one of the most important markups in our system ) .
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But typical OT grammars offer much richer finite-state models of left context ( Eisner 1997a ) than provided by the traditional HMM finite-state topologies .
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Other tools have been designed around particular techniques , such as finite state machines ( Karttunen et al. , 1997 ; Mohri et al. , 1998 ) .
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This contrasts with the findings described in Rapp & Zock ( 2010 ) where significant improvements could be achieved by increasing the number of source languages .
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The function selects the Value that removes most distractors , but in case of a tie , the least specific contestant is chosen , as long as it is not less specific than the basic-level Value ( i.e. , the most commonly occurring and psychologically most fundamental level , Rosch 1978 ) .
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Budanitsky and Hirst ( 2006 ) pointed out that distribution plots of judgments for the word pairs used by Rubenstein and Goodenough display an empty horizontal band that could be used to separate related and unrelated pairs .
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In fact , Reiter has even argued in favor of this approach , claiming that the interactions are sufficiently minor to be ignored ( or at least handled on an ad hoc basis ) ( Reiter 1994 ) .
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The method is called targeted self-training as it is similar in vein to self-training ( McClosky et al. , 2006 ) , with the exception that the new parse data is targeted to produce accurate word reorderings .
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In our previous work ( Zhang and Chai , 2009 ) , we started an initial investigation on conversation entailment .
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Bashir ( 1993 ) tried to construct a semantic analysis based on `` prepared '' and `` unprepared mind '' .
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It is also possible to focus on non-compositional compounds , a key point in bilingual applications ( Su et al. , 1994 ; Melamed , 1997 ; Lin , 99 ) .
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This is mainly due to the fact that Arabic is a non-concatenative language ( Al-Shalabi and Evens , 1998 ) , and that the stem/infix obtained by suppression of infix and prefix add-ons is not the same for words derived from the same origin called the root .
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