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 ) .


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 .


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 ) .


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 ) .


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 .


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 .


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 ) .


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 ) .


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 .


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 ) .


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 ) .


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 ) .


14We parse each sentence with the Collins parser ( Collins , 1999 ) .


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 .


We followed the same experimental procedure as discussed in ( Taft , 2004 ) for English polymorphemic words .


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 .


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 ) .


To address this problem , we are currently working on developing a metagrammar in the sense of ( Candito , 1999 ) .


Sentences like 12 , from Chomsky ( 1965 ) , are frequently cited .


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 .


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 .


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 .


Many other such cases are described in Danlos 's book ( Danlos 1987 ) .


â¢ 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 .


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 .


Experiments on Chinese SRL ( Xue and Palmer 2005 , Xue 2008 ) reassured these findings .


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 ) .


According to Budanitsky and Hirst ( 2006 ) , there are three prevalent approaches for evaluating SR measures : mathematical analysis , applicationspecific evaluation and comparison with human judgments .


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 ) .


A good study comparing document categorization algorithms can be found in ( Yang and Liu , 1999 ) .


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 ) .


We follow Stymne and Cancedda ( 2011 ) , for compound merging .


Semantic filters can also be used to prevent multiple versions of the same case frame ( Fillmore 1968 ) showing up as complements .


The terms have been identified as the most specific to our corpus by a program developed by Drouin ( 2003 ) and called TER1vloSTAT .


For statistical significance , we use McNemar 's test on non-gold LAS , as implemented by Nilsson and Nivre ( 2008 ) .


The availability of toolkits for this weighted case ( Mohri et al. , 1998 ; van Noord and Gerdemann , 2001 ) promises to unify much of statistical NLP .


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 .


We use a standard split of 268 training documents , 68 development documents , and 106 testing documents ( Culotta et al. , 2007 ; Bengtson and Roth , 2008 ) .


Bojar and Kos ( 2010 ) improved on this by marking prepositions with the case they mark ( one of the most important markups in our system ) .


But typical OT grammars offer much richer finite-state models of left context ( Eisner 1997a ) than provided by the traditional HMM finite-state topologies .


Other tools have been designed around particular techniques , such as finite state machines ( Karttunen et al. , 1997 ; Mohri et al. , 1998 ) .


This contrasts with the findings described in Rapp & Zock ( 2010 ) where significant improvements could be achieved by increasing the number of source languages .


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 ) .


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 .


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 ) .


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 .


In our previous work ( Zhang and Chai , 2009 ) , we started an initial investigation on conversation entailment .


Bashir ( 1993 ) tried to construct a semantic analysis based on `` prepared '' and `` unprepared mind '' .


It is also possible to focus on non-compositional compounds , a key point in bilingual applications ( Su et al. , 1994 ; Melamed , 1997 ; Lin , 99 ) .


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 .


ear regression adapted for classification ( Ting and Witten 1999 ) , which can be described by the following equation :


For example , the forward-backward algorithm ( Baum , 1972 ) trains only Hidden Markov Models , while ( Ristad and Yianilos , 1996 ) trains only stochastic edit distance .


Using the tree-cut technique described above , our previous work ( Tomuro , 2000 ) extracted systematic polysemy from WordNet .


( Och and Ney , 2002 ; Blunsom et al. , 2008 ) used maximum likelihood estimation to learn weights for MT. ( Och , 2003 ; Moore and Quirk , 2008 ; Zhao and Chen , 2009 ; Galley and Quirk , 2011 ) employed an evaluation metric as a loss function and directly optimized it .


5 Significant bigrams are obtained using the n-gram statistics package NSP ( Banerjee and Pedersen 2003 ) , which offers statistical tests to decide whether to accept or reject the null hypothesis regarding a bigram ( that it is not a collocation ) .


Liu et al. ( 2005 ) , Meral et al. ( 2007 ) , Murphy ( 2001 ) , Murphy and Vogel ( 2007 ) and Topkara et al. ( 2006a ) all belong to the syntactic transformation category .


2The WePS-1 corpus includes data from the Web03 testbed ( Mann , 2006 ) which follows similar annotation guidelines , although the number of document per ambiguous name is more variable .


The local training method ( Bottou and Vapnik , 1992 ) is widely employed in computer vision ( Zhang et al. , 2006 ; Cheng et al. , 2010 ) .


Recent work ( Banko and Brill , 2001 ; Curran and Moens , 2002 ) has suggested that some tasks will benefit from using significantly more data .


Rather than producing a complete analysis of sentences , the alternative is to perform only partial analysis of the syntactic structures in a text ( Harris , 1957 ; Abney , 1991 ; Greffenstette , 1993 ) .


The feasibility of automatically identifying outcome statements in secondary sources has been demonstrated by Niu and Hirst ( 2004 ) .


The standard approach is to train two models independently and then intersect their predictions ( Och and Ney 2003 ) .


We use the same method as Andrews et al. ( 2009 ) for generating our multimodal corpora : for each word token in the text corpus , a feature is selected stochastically from the word 's feature distribution , creating a word-feature pair .


MI was also recently used for inference-rule SPs by Pantel et al. ( 2007 ) .


Based on this advise ( Moore and Quirk , 2007 ) exclude the latent segmentation variables and opt for a heuristic training procedure .


For example , 10 million words of the American National Corpus ( Ide et al. , 2002 ) will have manually corrected POS tags , a tenfold increase over the Penn Treebank ( Marcus et al. , 1993 ) , currently used for training POS taggers .


The forward and backward probabilities , p0j and pkn , can be computed using single-source algebraic path for the simpler semiring ( R , + , x , â ) -- or equivalently , by solving a sparse linear system of equations over R , a much-studied problem at O ( n ) space , O ( nm ) time , and faster approximations ( Greenbaum , 1997 ) .


4To prove ( 1 ) â ( 3 ) , express f as an FST and apply the well-known Kleene-Sch Â¨ utzenberger construction ( Berstel and Reutenauer , 1988 ) , taking care to write each regexp in the construction as a constant times a probabilistic regexp .


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 .


Our work is more similar to NLG work that concentrates on structural constraints such as generative poetry ( Greene et al. , 2010 ) ( Colton et al. , 2012 ) ( Jiang and Zhou , 2008 ) or song lyrics ( Wu et al. , 2013 ) ( Ramakrishnan A et al. , 2009 ) , where specified meter or rhyme schemes are enforced .


Most DOP models , such as in Bod ( 1993 ) , Goodman ( 1996 ) , Bonnema et al. ( 1997 ) , Sima'an ( 2000 ) and Collins & Duffy ( 2002 ) , use a likelihood criterion in defining the best parse tree : they take ( some notion of ) the most likely ( i.e. most probable ) tree as a candidate for the best tree of a sentence .


The best performance on the WSJ corpus was achieved by a combination of the SATZ system ( Palmer and Hearst 1997 ) with the Alembic system ( Aberdeen et al. 1995 ) : a 0.5 % error rate .


The extracted frames are noisy as a result of parser errors and so are filtered using the binomial hypothesis theory ( BHT ) , following Brent ( 1993 ) .


This method allows the efficient retrieval of arbitrary length n-grams ( Nagao and Mori , 94 ; Haruno et al. , 96 ; Ikehaxa et al. , 96 ; Shimohata et al. , 1997 ; Russell , 1998 ) .


The current system learns finite state flowcharts whereas typical learning systems usually acquire coefficient values as in Minsky and Papert ( 1969 ) , assertional statements as in Michalski ( 1980 ) , or semantic nets as in Winston ( 1975 ) .


Our most accurate product model achieves an F score of 92.5 without the use of discriminative reranking and comes close to the best known numbers on this test set ( Zhang et al. , 2009 ) .


To demonstrate that this is possible we have implemented a system which constructs dictionary entries for the PATR-II system ( Shieber , 1984 and references therein ) .


Other works ( Kasper et al. , 1995 ; Becker and Lopez , 2000 ) convert HPSG grammars into LTAG grammars .


The work of Hearst ( 1996 ) demonstrates that faceted queries can be converted into simple filtering constraints to boost precision .


Efficient hardware implementation is also possible via chip-level parallelism ( Rote , 1985 ) .


2We could just as easily use other symmetric `` association '' measures , such as 02 ( Gale & Church , 1991 ) or the Dice coefficient ( Smadja , 1992 ) .


Krahmer and Theune ( 2002 ) have argued that Dale and Reiter 's ( 1995 ) dichotomy between salient and nonsalient objects ( where the objects in the domain are the salient ones ) should be replaced by an account that takes degrees of salience into account : No object can be too unsalient to be referred to , as long as the right properties are available .


The acquisition of dialogue as implemented in VNLCE is reminiscent of the program synthesis methodology developed by Biermann and Krishnaswamy ( 1976 ) where program flowcharts were constructed from traces of their behaviors .


Character classes , such as punctuation , are defined according to the Unicode Standard ( Aliprand et al. , 2004 ) .


Rather than producing a complete analysis of sentences , the alternative is to perform only partial analysis of the syntactic structures in a text ( Harris , 1957 ; Abney , 1991 ; Greffenstette , 1993 ) .


Finally , it has been shown by Groesser ( 1981 ) that the ratio of derived to explicit information necessary for understanding a piece of text is about 8:1 ; furthermore , our reading of the analysis of five paragraphs by Crothers ( 1979 ) strongly suggests that only the most direct or obvious inferences are being made in the process of building a model or constructing a theory of a paragraph .


In other methods , lexical resources are specifically tailored to meet the requirements of the domain ( Rosario and Hearst , 2001 ) or the system ( Gomez , 1998 ) .


The exact form of M ( Si ) need not be discussed at this point ; it could be a conceptual dependence graph ( Schank and Abelson 1977 ) , a deep parse of Si , or some other representation .


Some methods are based on likelihood ( Och and Ney , 2002 ; Blunsom et al. , 2008 ) , error rate ( Och , 2003 ; Zhao and Chen , 2009 ; Pauls et al. , 2009 ; Galley and Quirk , 2011 ) , margin ( Watanabe et al. , 2007 ; Chiang et al. , 2008 ) and ranking ( Hopkins and May , 2011 ) , and among which minimum error rate training ( MERT ) ( Och , 2003 ) is the most popular one .


Similarly , ( Barzilay and Lee , 2003 ) and ( Shinyanma et al. , 2002 ) learn sentence level paraphrase templates from a corpus of news articles stemming from different news source .


This setup is also scalable to a higher number of word pairs ( 350 ) as was shown in Gurevych ( 2006 ) .


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 .


Louwerse et al. ( 2006 ) and Louwerse et al. ( 2007 ) study the relation between eye gaze , facial expression , pauses and dialogue structure in annotated English map-task dialogues ( Anderson et al. , 1991 ) and find correlations between the various modalities both within and across speakers .


Some examples include text categorization ( Lewis and Catlett 1994 ) , base noun phrase chunking ( Ngai and Yarowsky 2000 ) , part-of-speech tagging ( Engelson Dagan 1996 ) , spelling confusion set disambiguation ( Banko and Brill 2001 ) , and word sense disambiguation ( Fujii et al. 1998 ) .


It is known that certain cue words and phrases ( Hirschberg and Litman 1993 ) can serve as explicit indicators of discourse structure .


The last point may be seen better if we look at some differences between our system and KRYPTON , which also distinguishes between an object theory and background knowledge ( cfXXX Brachman et al. 1985 ) .


One approach to this problem is that taken by the ASCOT project ( Akkerman et al. , 1985 ; Akkerman , 1986 ) .


Though we could have used a further downstream measure like BLEU , METEOR has also been shown to directly correlate with translation quality ( Banerjee and Lavie , 2005 ) and is simpler to measure .


For all experiments reported in this section we used the syntactic dependency parser MaltParser v1 .3 ( Nivre 2003 , 2008 ; KÃ¼bler , McDonald , and Nivre 2009 ) , a transition-based parser with an input buffer and a stack , which uses SVM classifiers


We conducted experiments with gold features to assess the potential of these features , and with predicted features , obtained from training a simple maximum likelihood estimation classifier on this resource ( Alkuhlani and Habash 2012 ) .19 The first part of Table 8 shows that the RAT ( rationality ) feature is very relevant ( in gold ) , but suffers from low accuracy ( no gains in machine-predicted input ) .


In our previous work ( Salloum and Habash , 2011 ; Salloum and Habash , 2012 ) , we applied our approach to tokenized Arabic and our DA-MSA transfer component used feature transfer rules only .


It has already been used to implement a framework for teaching NLP ( Loper and Bird , 2002 ) .


Due to their remarkable ability to incorporate context structure information and long distance reordering into the translation process , tree-based translation models have shown promising progress in improving translation quality ( Liu et al. , 2006 , 2009 ; Quirk et al. , 2005 ; Galley et al. , 2004 , 2006 ; Marcu et al. , 2006 ; Shen et al. , 2008 ; Zhang et al. , 2011b ) .


Liu et al. ( 2005 ) , Meral et al. ( 2007 ) , Murphy ( 2001 ) , Murphy and Vogel ( 2007 ) and Topkara et al. ( 2006a ) all belong to the syntactic transformation category .


Similarly , the notion of R + M-abduction is spiritually related to the `` abductive inference '' of Reggia ( 1985 ) , the `` diagnosis from first principles '' of Reiter ( 1987 ) , `` explainability '' of Poole ( 1988 ) , and the subset principle of Berwick ( 1986 ) .


On the other side , wikis started as collective works where each entry is not owned by a single author e.g. Wikipedia ( 2005 ) .


To address this inconsistency in the correspondence between inflectional features and morphemes , and inspired by SmrÅ¾ ( 2007 ) , we distinguish between two types of inflectional features : formbased ( a.k.a. surface , or illusory ) features and functional features .6 Most available Arabic NLP tools and resources model morphology using formbased ( `` surface '' ) inflectional features , and do not mark rationality ; this includes the Penn Arabic Treebank ( PATB ) ( Maamouri et al. 2004 ) , the Buckwalter morphological analyzer ( Buckwalter 2004 ) , and tools using them such as the Morphological Analysis and Disambiguation for Arabic ( MADA ) toolkit ( Habash and Rambow 2005 ; Habash , Rambow , and Roth 2012 ) .


Jiang et al. ( 2005 ) has built a semantic role classifier exploiting the interdependence of semantic roles .


Others have applied the NLP technologies of near-duplicate detection and topic-based text categorization to politically oriented text ( Yang and Callan , 2005 ; Purpura and Hillard , 2006 ) .


8 It is based on the dataset of Pang and Lee ( 2004 ) ,9 which consists of 1000 positive and 1000 negative movie reviews , tokenized and divided into 10 folds ( F0 -- F9 ) .


In previous work ( Bachenko et al. 1986 ) , we described an experimental text-to-speech system that determined prosodic phrasing for the Olive -- Liberman synthesizer ( Olive and Liberman 1985 ) .


The UMLS -- the Unified Medical Language System ( UMLS ) has been developed and maintained by National Library of Medicine ( NLM ) [ 17 ] .


The data used in the experiment was selected from the Penn Treebank Wall Street Journal , and is the same used by Brill and Wu ( 1998 ) .


As shown in Meurers ( 1994 ) this is a well-motivated convention since it avoids splitting up lexical rules to transfer the specifications that must be preserved for different lexical entries .


The reader may consult recent papers on this subject ( e.g. Moens and Steedman 1987 ; Webber 1987 ) to see what a formal interpretation of events in time might look like .


Proceedings of EACL '99 example , the ALE parser ( Carpenter and Penn , 1994 ) presupposes a phrase structure backbone which can be used to determine whether a constraint is to be interpreted bottom-up or topdown .


Following Soon et al. ( 2001 ) , we represent use the ACE training data for acquiring our SC clasSCA as a binary value that indicates whether the insifier ; instead , we use the BBN Entity Type Corpus duced SCs of the two NPs involved are the same or ( Weischedel and Brunstein , 2005 ) , which consists of not .


Following Ratinov and Roth ( 2009 ) , we also compare the performance of our system with a system using features based on the Brown clusters of the word types in a document .


Church and Hanks ( 1990 ) use mutual information to identify collocations , a method they claim is reasonably effective for words with a frequency of not less than five .


We do this with a first-order HMM part-ofspeech tagger ( Merialdo [ 13 ] ) .


Using the bottom-up , dynamic programming technique ( see the appendix for details ) of computing inside probabilities ( Lari and Young 1990 ) , we can efficiently compute the probability of the sentence , P ( w | G ) .


As shown in ( Minnen , 1996 ) â¢ The presented research was carried out at the University of Tubingen , Germany , as part of the Sonderforschungsbereich 340 .


According to Hinds ( 1979 ) , paragraphs are made up of segments , which in turn are made up of sentences or clauses , which in turn are made up of phrases .


Similarly , the notion of R + M-abduction is spiritually related to the `` abductive inference '' of Reggia ( 1985 ) , the `` diagnosis from first principles '' of Reiter ( 1987 ) , `` explainability '' of Poole ( 1988 ) , and the subset principle of Berwick ( 1986 ) .


This choice is motivated by an observation we made previously ( Hasan and Ng , 2013a ) : since each post in a sequence is a reply to the preceding post , we could exploit their dependencies by determining their stance labels together .3 As our sequence learner , we employ a maximum entropy Markov model ( MEMM ) ( McCallum et al. , 2000 ) .


Over the past decade , researchers at IBM have developed a series of increasingly sophisticated statistical models for machine translation ( Brown et al. , 1988 ; Brown et al. , 1990 ; Brown et al. , 1993a ) .


This may be because pipelines have many engineering advantages , and in practice the sort of problems pointed out by Danlos and other pipeline critics do not seem to be a major problem in current applied NLG systems ( Mittal et al. 1998 ) .


This approach has its roots in Fillmore 's Case Grammar ( 1968 ) , and serves as the foundation for two current large-scale semantic annotation projects : FrameNet ( Baker et al. , 1998 ) and PropBank ( Kingsbury et al. , 2002 ) .


Two exceptions to this generalisation are the Linguistic String Project ( Sager , 1981 ) and the IBM CRITIQUE ( formerly EPISTLE ) Project ( Heidorn et al. , 1982 ; Byrd , 1983 ) ; the former employs a dictionary of approximately 10,000 words , most of which are specialist medical terms , the latter has well over 100,000 entries , gathered from machine readable sources .


They can also shift the dialogue 2The notion of the initiative in this paper is different from that of the dialogue initiative of Chu-Carroll ( 2000 ) .


The Google n-gram data was collected by Google Research for statistical language modelling , and has been used for many tasks such as lexical disambiguation ( Bergsma et al. , 2009 ) , and contains English n-grams and their observed frequency counts , for counts of at least 40 .


Withindocument coreference resolution has been applied to produce summaries of text surrounding occurrences of the name ( Bagga and Baldwin , 1998 ; Gooi and Allan , 2004 ) .


To represent the semantics of predicative units , we use FrameNet inventory of frames and frame elements ( C.Johnson et al. , 2002 ) .


Similar observation for surface word frequency was also observed by ( Bertram et al. , 2000 ; Bradley , 1980 ; Burani et al. , 1987 ; Burani et al. , 1984 ; Schreuder et al. , 1997 ; Taft 1975 ; Taft , 2004 ) where it has been claimed that words having low surface frequency tends to decompose .


These two sets of data were used for automatic dialogue act classification , which was run in the Weka system ( Witten and Frank , 2005 ) .


â¢ The transition probability a is 0.7 using the EM algorithm ( Rabiner , 1989 ) on the TREC4 ad-hoc query set .


Sridhar et al. ( 2009 ) obtain promising results in dialogue act tagging of the Switchboard-DAMSL corpus using lexical , syntactic and prosodic cues , while Gravano and Hirschberg ( 2009 ) examine the relation between particular acoustic and prosodic turn-yielding cues and turn taking in a large corpus of task-oriented dialogues .


( Yang and Pedersen , 1997 ) has found strong correlations between DF , IG and the X2 statistic for a term .


Despite this , to date , there has been little work on corpus-based approaches to help-desk response automation ( notable exceptions are Carmel , Shtalhaim , and Soffer 2000 ; Lapalme and Kosseim 2003 ; Bickel and Scheffer 2004 ; Malik , Subramaniam , and Kaushik 2007 ) .


To quantify the relative strengths of these transitive inferences , Shaw and Hatzivassiloglou ( 1999 ) propose to assign a weight to each link .


While these approaches have been reasonably successful ( see Mitkov ( 2002 ) ) , Kehler et al. ( 2004 ) speculate that deeper linguistic knowledge needs to be made available to resolvers in order to reach the next level of performance .


Lisp is not particularly well suited for interfacing to complex , structured objects , and it was not our intention to embark on a major effort involving the development of a formal model of a dictionary ( of the style described in , eg. , Tompa 1986 ) ; on the other hand a method of access was clearly required , which was flexible enough to support a range of applications intending to make use of the LDOCE tape .


We train a 4-gram language model on the Xinhua portion of the English Gigaword corpus using the SRILM Toolkits ( Stolcke , 2002 ) with modified Kneser-Ney smoothing ( Chen and Goodman , 1998 ) .


â¢ Learnability ( Zernik and Dyer 1987 ) â¢ Text generation ( Hovy 1988 ; Milosavljevic , Tulloch , and Dale 1996 ) â¢ Speech generation ( Rayner and Carter 1997 ) â¢ Localization ( Sch Â¨ aler 1996 )


Details of the top performing heuristics of COCKTAIL were reported in ( Harabagiu and Maiorano , 1999 ) .


Representative systems are described in Boisen et al. ( 1989 ) , De Mattia and Giachin ( 1989 ) , Niedermair ( 1989 ) , Niemann ( 1990 ) , and Young ( 1989 ) .


In addition , Moulin et al. ( 1985 ) note that our Object Raising rule would assign mean to this category incorrectly .


The parallel corpus is word-aligned using GIZA + + ( Och and Ney , 2003 ) .


tions for the remaining 20 % of the instances ; and ( 3 ) train an SVM classifier ( using the LIBSVM package ( Chang and Lin , 2001 ) ) on these 20 % of the instances , where each instance , i , is represented by a set of 31 binary features .


Our algorithm is similar to the approach taken by Pereira and Schabes ( 1992 ) for inducing PCFG parsers .


Recently , several alternative , often quite sophisticated approaches to collective classification have been proposed ( Neville and Jensen , 2000 ; Lafferty et al. , 2001 ; Getoor et al. , 2002 ; Taskar et al. , 2002 ; Taskar et al. , 2003 ; Taskar et al. , 2004 ; McCallum and Wellner , 2004 ) .


This experiment was again replicated by Resnik ( 1995 ) with 10 subjects .


Children use vague adjectives among their first dozens of words ( Peccei 1994 ) and understand some of their intricacies as early as their 24th month ( Ebeling and Gelman 1994 ) .


Other approaches use less deep linguistic resources ( e.g. , POS-tags Stymne ( 2008 ) ) or are ( almost ) knowledge-free ( e.g. , Koehn and Knight ( 2003 ) ) .


This includes work on question answering ( Wang et al. , 2007 ) , sentiment analysis ( Nakagawa et al. , 2010 ) , MT reordering ( Xu et al. , 2009 ) , and many other tasks .


( 4 ) NE : We use BBN 's IdentiFinder ( Bikel et al. , 1999 ) , a MUC-style NE recognizer to determine the NE type of NPZ .


Yi et al. ( 2007 ) has made the first attempt working on the single semantic role level to make further improvement .


In particular , since we treat each individual speech within a debate as a single `` document '' , we are considering a version of document-level sentiment-polarity classification , namely , automatically distinguishing between positive and negative documents ( Das and Chen , 2001 ; Pang et al. , 2002 ; Turney , 2002 ; Dave et al. , 2003 ) .


raw length value as a feature , we follow our previous work ( Rubino et al. , 2013 ; Wagner et al. , 2014 ) and create multiple features for length using a decision tree ( J48 ) .


Williams and Koehn ( 2011 ) used unification in an SMT system to model some of the


Following Ruch et al. ( 2003 ) and Barzilay and Lee ( 2004 ) , we employed Hidden Markov Models to model the discourse structure of MEDLINE abstracts .


The language grounding problem has received significant attention in recent years , owed in part to the wide availability of data sets ( e.g. Flickr , Von Ahn ( 2006 ) ) , computing power , improved computer vision models ( Oliva and Torralba , 2001 ; Lowe , 2004 ; Farhadi et al. , 2009 ; Parikh and Grauman , 2011 ) and neurological evidence of ties between the language , perceptual and motor systems in the brain ( Pulverm Â¨ uller et al. , 2005 ; Tettamanti et al. , 2005 ; Aziz-Zadeh et al. , 2006 ) .


Due to their remarkable ability to incorporate context structure information and long distance reordering into the translation process , tree-based translation models have shown promising progress in improving translation quality ( Liu et al. , 2006 , 2009 ; Quirk et al. , 2005 ; Galley et al. , 2004 , 2006 ; Marcu et al. , 2006 ; Shen et al. , 2008 ; Zhang et al. , 2011b ) .


Previous work has argued that initiative affects the degree of control an agent has in the dialogue interaction ( Whittaker and Stenton , 1988 ; Walker and Whittaker , 1990 ; Chu-Carroll and Brown , 1998 ) .


Many provide graphical user interfaces ( GUI ) for manual annotation ( e.g. General Architecture for Text Engineering ( GATE ) ( Cunningham et al. , 1997 ) and the Alembic Workbench ( Day et al. , 1997 ) ) as well as NLP tools and resources that can be manipulated from the GUI .


A number of speech understanding systems have been developed during the past fifteen years ( Barnett et al. 1980 , Dixon and Martin 1979 , Erman et al. 1980 , Haton and Pierrel 1976 , Lea 1980 , Lowerre and Reddy 1980 , Medress 1980 , Reddy 1976 , Walker 1978 , and Wolf and Woods 1980 ) .


It allows the construction of a non-TAL ( Shieber , 1994 ) , ( Harbusch & Poller , 2000 ) .


In addition , the advantages of using linguistically annotated data over raw data are well documented ( Mair , 2005 ; Granger and Rayson , 1998 ) .


In particular , the `` Semantic Information Retrieval '' project ( SIR Project , 2006 ) systematically investigates the use of lexical-semantic relations between words or concepts for improving the performance of information retrieval systems .


Our re-ranking approach , like the approach to parse re-ranking of Collins ( 2000 ) , employs a simpler model -- a local semantic role labeling algorithm -- as a first pass to generate a set of n likely complete assignments of labels to all parse tree nodes .


For instance , the Alembic workbench ( Aberdeen et al. 1995 ) contains a sentence-splitting module that employs over 100 regular-expression rules written in Flex .


In contrast , a single statistical model allows one to maintain a single table ( Langkilde , 2000 ) .


Our experiments are based on the multimodal extension of Latent Dirichlet Allocation developed by Andrews et al. ( 2009 ) .


First , it has been noted that in many natural language applications it is sufficient to use shallow parsing information ; information such as noun phrases ( NPs ) and other syntactic sequences have been found useful in many large-scale language processing applications including information extraction and text summarization ( Grishman , 1995 ; Appelt et al. , 1993 ) .


Cohn and Blunsom ( 2009 ) adopted a Bayesian method to infer an STSG by exploring the space of alignments based on parse trees .


In corpus linguistics building such megacorpora is beyond the scope of individual researchers , and they are not easily accessible ( Kennedy , 1998 : 56 ) unless the web is used as a corpus ( Kilgarriff and Grefenstette , 2003 ) .


In addition , there are a number of projects under way to develop substantial lexicons from machine readable sources ( see Boguraev , 1986 for details ) .


We carried out two parallel experiments with two parsers available for Czech , parser I ( Hajie et al. , 1998 ) and parser II ( Charniak , 1999 ) .


Part of speech taggers typically require input in the format of a single sentence per line ( for example Brill 's tagger ( Brill , 1992 ) ) and parsers generally aim to produce a tree spanning each sentence .


The elimination of redundant nondeterminism is based on Unfold/Fold transformation techniques ( Tamaki and Sato 1984 ) .29 The unfolding transformation is also referred to as partial execution , for example , by Pereira and Shieber ( 1987 ) .


Problems such as these have motivated research on more abstract , dependencybased parser evaluation ( e.g. , Lin 1995 ; Carroll , Briscoe , and Sanfilippo 1998 ; Carroll et al. 2002 ; Clark and Hockenmaier 2002 ; King et al. 2003 ; Preiss 2003 ; Kaplan et al. 2004 ; Miyao and Tsujii 2004 ) .


This seems to provide additional evidence of Bruni et al. ( 2012b ) 's suggestion that something like a distributional hypothesis of images is plausible .


For instance , GATE currently provides a POS tagger , named entity recogniser and gazetteer and ontology editors ( Cunningham et al. , 2002 ) .


Latent variables we wish to consider are an increased number of word classes ; more flexible regions -- see Petrov et al. ( 2007 ) on learning a state transition diagram for acoustic regions in phone recognition -- and phonological features and syllable boundaries .


Since earlier versions of the SNoW based CSCL were used only to identify single phrases ( Punyakanok and Roth , 2001 ; Munoz et al. , 1999 ) and never to identify a collection of several phrases at the same time , as we do here , we also trained and tested it under the exact conditions of CoNLL-2000 ( Tjong Kim Sang and Buchholz , 2000 ) to compare it to other shallow parsers .


Using the implicit modeling of argument consistency , we follow the same approach as in our previous work ( Zhang and Chai , 2009 ) and trained a logistic regression model to predict verb alignment based on the features in Table 1 .


Recent developments in linguistics , and especially on grammatical theory -- for example , Generalised Phrase Structure Grammar ( GPSG ) ( Gazdar et al. , 1985 ) , Lexical Functional Grammar ( LFG ) ( Kaplan and Bresnan , 1982 ) -- and on natural language parsing frameworks -- for example , Functional Unification Grammar ( FUG ) ( Kay , 1984a ) , PATR-II ( Shieber , 1984 ) -- make it feasible to consider the implementation of efficient systems for the syntactic analysis of substantial fragments of natural language .


We train a 4-gram language model on the Xinhua portion of the English Gigaword corpus using the SRILM Toolkits ( Stolcke , 2002 ) with modified Kneser-Ney smoothing ( Chen and Goodman , 1998 ) .


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 ) .


This deficiency is rectified in the verb classification system employed by Jackendoff and Grimshaw ( 1985 ) in the Brandeis verb catalogue .


Previous work has argued that initiative affects the degree of control an agent has in the dialogue interaction ( Whittaker and Stenton , 1988 ; Walker and Whittaker , 1990 ; Chu-Carroll and Brown , 1998 ) .


1990 ) , on linguisitic acquisition ( by the use of Part-of-Speech filters hand-crafted by a linguist ) ( Oueslati , 1999 ) or , more frequently , on a combination of the two ( Smadja , 1993 ; Kilgarriff and Tugwell , 2001 , for example ) .


It is frequently used in tasks like scene identification , and Deselaers and Ferrari ( 2011 ) shows that distance in GIST space correlates well with semantic distance in WordNet .


Because each rule r consists of a target tree fragment frag and a source string str in the model , we follow Cohn and Blunsom ( 2009 ) and decompose the prior probability P0 ( r | N ) into two factors as follows :


To address this inconsistency in the correspondence between inflectional features and morphemes , and inspired by SmrÅ¾ ( 2007 ) , we distinguish between two types of inflectional features : formbased ( a.k.a. surface , or illusory ) features and functional features .6 Most available Arabic NLP tools and resources model morphology using formbased ( `` surface '' ) inflectional features , and do not mark rationality ; this includes the Penn Arabic Treebank ( PATB ) ( Maamouri et al. 2004 ) , the Buckwalter morphological analyzer ( Buckwalter 2004 ) , and tools using them such as the Morphological Analysis and Disambiguation for Arabic ( MADA ) toolkit ( Habash and Rambow 2005 ; Habash , Rambow , and Roth 2012 ) .


In our prior work ( Xiong and Litman , 2011 ) , we examined whether techniques used for predicting the helpfulness of product reviews ( Kim et al. , 2006 ) could be tailored to our peer-review domain , where the definition of helpfulness is largely influenced by the educational context of peer review .


Previous sentiment-analysis work in different domains has considered inter-document similarity ( Agarwal and Bhattacharyya , 2005 ; Pang and Lee , 2005 ; Goldberg and Zhu , 2006 ) or explicit


Bruni et al. ( 2012a ) show how a BoVW model may be easily combined with a distributional vector space model of language using only vector concatenation .


The following are the various tag sets we use in this article : ( a ) the core POS tag sets CORE44 and the newly introduced CORE12 ; ( b ) CATiB Treebank tag set ( CATIB6 ) ( Habash and Roth 2009 ) and its newly introduced extension of CATIBEX created using simple regular expressions on word form , indicating particular morphemes such as the prefix JI Al + or the suffix v ' + wn ; this tag set is the best-performing tag set for Arabic on predicted values as reported in Section 4 ; ( c ) the PATB full tag set with complete morphological tag ( BW ) ( Buckwalter 2004 ) ; and two extensions of the PATB reduced tag set ( PENN POS , a.k.a. RTS , size 24 [ Diab , Hacioglu , and Jurafsky 2004 ] ) , both outperforming it : ( d ) Kulick , Gabbard , and Marcus ( 2006 ) 's tag set ( KULICK ) , size 43 , one of whose most important extensions is the marking of the definite article clitic , and ( e ) Diab and Benajiba 's ( in preparation ) EXTENDED RTS tag set ( ERTS ) , which marks gender , number , and definiteness , size 134 .


The numeral ( whether it is implicit , as in ( 3 ) , or explicit ) can be construed as allowing the reader to draw inferences about the standards employed ( Kyburg and Morreau 2000 ; DeVault and Stone 2004 ) : ( 3 ) , for example , implies a standard that counts 10 cm as large and 8 cm as not large .


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 .


On the WSJ corpus our system performed slightly better than the combination of the Alembic and SATZ systems described in Palmer and Hearst ( 1997 ) ( 0.44 % vs. 0.5 % error rate ) .


Sanderson , 1994 studied the issue of disambiguation for mono-lingual M.


Recently , several alternative , often quite sophisticated approaches to collective classification have been proposed ( Neville and Jensen , 2000 ; Lafferty et al. , 2001 ; Getoor et al. , 2002 ; Taskar et al. , 2002 ; Taskar et al. , 2003 ; Taskar et al. , 2004 ; McCallum and Wellner , 2004 ) .


Although in this paper we take modus ponens as the main rule of inference , in general one can consider deductive closures with respect to weaker , nonstandard logics , ( cfXXX Levesque 1984 ; Frisch 1987 ; Patel-Schneider 1985 ) .


Riehemann 1993 ; Oliva 1994 ; Frank 1994 ; Opalka 1995 ; Sanfilippo 1995 ) .


Berger et al. 2000 ; Jijkoun and de Rijke 2005 ; Soricut and Brill 2006 ) .


We will examine the worst-case complexity of interpretation as well as generation to shed some light on the hypothesis that vague descriptions are more difficult to process than others because they involve a comparison between objects ( Beun and Cremers 1998 , Krahmer and Theune 2002 ) .


A number of proposals in the 1990s deliberately limited the extent to which they relied on domain and/or linguistic knowledge and reported promising results in knowledge-poor operational environments ( Dagan and Itai 1990 , 1991 ; Lappin and Leass 1994 ; Nasukawa 1994 ; Kennedy and Boguraev 1996 ; Williams , Harvey , and Preston 1996 ; Baldwin 1997 ; Mitkov 1996 , 1998b ) .


From the Meaning-Text Theory ( MTT ) 1 point of view , Natural Language ( NL ) is considered as a correspondence between meanings and texts ( Kahane , 2001 ) .


This means that natural language expressions such as `` A is B , '' `` A is the same as B , '' etc. are not directly represented by logical equality ; similarly , `` not '' is often not treated as logical negation ; cfXXX Hintikka ( 1985 ) .


The full-listing model claims that polymorphic words are represented as a whole in the human mental lexicon ( Bradley , 1980 ; Butterworth , 1983 ) .


As for work on Arabic ( MSA ) , results have been reported on the PATB ( Kulick , Gabbard , and Marcus 2006 ; Diab 2007 ; Green and Manning 2010 ) , the Prague Dependency Treebank ( PADT ) ( Buchholz and Marsi 2006 ; Nivre 2008 ) and the CATiB ( Habash and Roth 2009 ) .


However , learning-based resolvers have not been able to benefit from having an SC agreement feature , presumably because the method used to compute the SC of an NP is too simplistic : while the SC of a proper name is computed fairly accurately using a named entity ( NE ) recognizer , many resolvers simply assign to a common noun the first ( i.e. , most frequent ) WordNet sense as its SC ( e.g. , Soon et al. ( 2001 ) , Markert and Nissim ( 2005 ) ) .


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 ) .


The ability to explicitly identify these sections in unstructured text could play an important role in applications such as document summarization ( Teufel and Moens , 2000 ) , information retrieval ( Tbahriti et al. , 2005 ) , information extraction ( Mizuta et al. , 2005 ) , and question answering .


Many statistical parsers ( Ratnaparkhi , 1999 ; Collins , 1999 ; Charniak , 2001 ) are based on a history-based probability model ( Black et al. , 1993 ) , where the probability of each decision in a parse is conditioned on the previous decisions in the parse .


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 ) .


For instance , ( Lin and Pantel , 2001 ) acquire two-argument templates ( inference rules ) from corpora using an extended version of the distributional analysis in which paths in dependency trees that have similar arguments are taken to be close in meaning .


Per-state joint normalization ( Eisner , 2001b , Â§ 8.2 ) is similar but drops the dependence on a .


Other studies on the value of disambiguation for cross-lingual IR include Hiemstra and de Jong , 1999 ; Hull , 1997 .


We have not yet made use of TINA 'S probabilities in adjusting the recognizer scores on the fly , but we have been able to incorporate linguistic scores to resort N-best outputs , giving a significant improvement in performance ( Goodine et al. 1991 ) .


These features are carefully designed to reduce the data sparseness problem and some of them are inspired by previous work ( He et al. , 2008 ; Gimpel and Smith , 2008 ; Marton and Resnik , 2008 ; Chiang et al. , 2009 ; Setiawan et al. , 2009 ; Shen et al. , 2009 ; Xiong et al. , 2009 ) : 1 .


Nevertheless , the full document text is present in most systems , sometimes as the only feature ( Sugiyama and Okumura , 2007 ) and sometimes in combination with others see for instance ( Chen and Martin , 2007 ; Popescu and Magnini , 2007 ) - .


More recently , ( Sebastiani , 2002 ) has performed a good survey of document categorization ; recent works can also be found in ( Joachims , 2002 ) , ( Crammer and Singer , 2003 ) , and ( Lewis et al. , 2004 ) .


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 ) .


It is these orthographic variations and complex morphological structure that make Arabic language processing challenging ( Xu et al. , 2001 ; Xu et al. , 2002 ) .


A number of speech understanding systems have been developed during the past fifteen years ( Barnett et al. 1980 , Dixon and Martin 1979 , Erman et al. 1980 , Haton and Pierrel 1976 , Lea 1980 , Lowerre and Reddy 1980 , Medress 1980 , Reddy 1976 , Walker 1978 , and Wolf and Woods 1980 ) .


It has been more difficult showing that agreement morphology helps parsing , however , with negative results for dependency parsing in several languages ( Eryigit , Nivre , and Oflazer 2008 ; Nivre , Boguslavsky , and Iomdin 2008 ; Nivre 2009 ) .


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 ) .


This idea was proposed by Krauwer and des Tombe ( 1981 ) , Langendoen and Langsam ( 1987 ) , and Pulman ( 1986 ) , and was rediscovered by Black ( 1989 ) and recently by Johnson ( 1998 ) .


A nonprobabilistic approach for DA labeling proposed by Samuel , Carberry , and Vijay-Shanker ( 1998 ) is transformation-based learning ( Brill 1993 ) .


However , since work in this direction has started , a significant progress has also been made in the research on statistical learning of full parsers , both in terms of accuracy and processing time ( Charniak , 1997b ; Charniak , 1997a ; Collins , 1997 ; Ratnaparkhi , 1997 ) .


Some methods are based on likelihood ( Och and Ney , 2002 ; Blunsom et al. , 2008 ) , error rate ( Och , 2003 ; Zhao and Chen , 2009 ; Pauls et al. , 2009 ; Galley and Quirk , 2011 ) , margin ( Watanabe et al. , 2007 ; Chiang et al. , 2008 ) and ranking ( Hopkins and May , 2011 ) , and among which minimum error rate training ( MERT ) ( Och , 2003 ) is the most popular one .


The algorithm we implemented is inspired by the work of Yarowsky ( 1995 ) on word sense disambiguation .


Various approaches for computing semantic relatedness of words or concepts have been proposed , e.g. dictionary-based ( Lesk , 1986 ) , ontology-based ( Wu and Palmer , 1994 ; Leacock and Chodorow , 1998 ) , information-based ( Resnik , 1995 ; Jiang and Conrath , 1997 ) or distributional ( Weeds and Weir , 2005 ) .


EM maximizes G ( 0 ) via block-coordinate ascent on a lower bound F ( q , 0 ) using an auxiliary distribution over the latent variables q ( z | x , y ) ( Neal and Hinton 1998 ) :


It has been argued that generating such modifiers is not a trivial decision because it interferes with the planning of both local and global coherence ( in the sense of ( Grosz and Sidner , 1986 ) ) ( Cheng and Mellish , 2000a ) .


â¢ Only qualitative observations of the responses were reported ( no formal evaluation was performed ) ( Lapalme and Kosseim 2003 ; Roy and Subramaniam 2006 ) .


A stops B from doing something ; A disagreees with B on something , 8 % and 12 % ) Note that in our original work ( Zhang and Chai , 2009 ) , only development data were used to show some initial observations .


We evaluated on the English CCGBank ( Hockenmaier and Steedman , 2007 ) , which is a transformation of the Penn Treebank ( Marcus et al. , 1993 ) ; the CTBCCG ( Tse and Curran , 2010 ) transformation of the Penn Chinese Treebank ( Xue et al. , 2005 ) ; and the CCG-TUT corpus ( Bos et al. , 2009 ) , built from the TUT corpus of Italian text ( Bosco et al. , 2000 ) .


The EM algorithm ( Dempster et al. , 1977 ) can maximize these functions .


Finally , feedback expressions ( head nods and shakes ) are successfully predicted from speech , prosody and eye gaze in interaction with Embodied Communication Agents as well as human communication ( Fujie et al. , 2004 ; Morency et al. , 2005 ; Morency et al. , 2007 ; Morency et al. , 2009 ) .


For these or for a specific domain , basic synonymic dictionaries can be complemented using learning methods based on distributional similarity ( Pereira et al. , 1993 ; Lin , 1998 ) .


For projective parsing , it is significantly faster than exact dynamic programming , at the cost of small amounts of search error , We are interested in extending these ideas to phrase-structure and lattice parsing , and in trying other higher-order features , such as those used in parse reranking ( Charniak and Johnson , 2005 ; Huang , 2008 ) and history-based parsing ( Nivre and McDonald , 2008 ) .


The coreference system system is similar to the Bell tree algorithm as described by ( Luo et al. , 2004 ) .


Other representations use the link structure ( Malin , 2005 ) or generate graph representations of the extracted features ( Kalashnikov et al. , 2007 ) .


The research described below is taking place in the context of three collaborative projects ( Boguraev , 1987 ; Russell et al. , 1986 ; Phillips and Thompson , 1986 ) to develop a general-purpose , wide coverage morphological and syntactic analyser for English .


We experiment with four learners commonly employed in language learning : Decision List ( DL ) : We use the DL learner as described in Collins and Singer ( 1999 ) , motivated by its success in the related tasks of word sense disambiguation ( Yarowsky , 1995 ) and NE classification ( Collins and Singer , 1999 ) .


transition-based dependency parsing framework ( Nivre , 2008 ) using an arc-eager transition strategy and are trained using the perceptron algorithm as in Zhang and Clark ( 2008 ) with a beam size of 8 .


Using the basic solution proposed by ( Mehdad et al. , 2010 ) as a term of comparison , we experiment with different sources of multilingual lexical knowledge to address the following questions : ( 1 ) What is the potential of the existing multilingual lexical resources to approach CLTE ?


Acoustic models for HTK is trained with the continuous speech database of the Acoustical Society of Japan ( Kobayashi et al. , 1992 ) .


Automatic text categorization has been used in search engines , digital library systems , and document management systems ( Yang , 1999 ) .


For our Text modality , we use deWaC , a large German web corpus created by the WaCKy group ( Baroni et al. , 2009 ) containing approximately 1.7 B word tokens .


Unless very high rates of misspellings are to be expected ( this explains the favorable results for trigram indexing in ( Franz et al. , 2000 ) ) one can not really recommend this method .


For english , there is for instance the 15 year old HewlettPackard test suite , a simple text file listing test sentences and grouping them according to linguistics phenomena ( Flickinger et al. , 1987 ) ; and more recently , the much more sophisticated TSNLP ( Test Suite for Natural Language Processing ) which includes some 9500 test items for English , French and German , each of them being annotated with syntactic and application related information ( Oepen and Flickinger , 1998 ) .


Previous work on Chinese SRL mainly focused on how to transplant the machine learning methods which has been successful with English , such as Sun and Jurafsky ( 2004 ) , Xue and Palmer ( 2005 ) and Xue ( 2008 ) .


A similar method is included in PATR-II ( Shieber et al. 1983 ) and can be used to encode lexical rules as binary relations in the CUF system ( Dorre and Eisele 1991 ; Done and Dorna 1993b ) or the TFS system ( Emele and Zajac 1990 ; Emele 1994 ) .


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 ) .


With the use of computers in storing the explosive amount of biological information , natural language processing ( NLP ) approaches have been explored to make the task of managing information recorded in free text more feasible [ 1 , 2 ] .


A formula q5 of L ( =-RRB- , the language with equality , is weakly R + M-abductible from an object theory T , denoted by T I-R + m 0 , iff there exists a partial theory T e PT ( T ) and a preferred model M E PM ( T ) such that M = 0 , i.e. 0 is true in at least one preferred model of the partial theory T. Note : The notions of strong provability and strong R + M-abduction can be introduced by replacing `` there exists '' by `` all '' in the above definitions ( cfXXX Zadrozny 1987b ) .


The first version ( TIMIT ) was developed for the 450 phonetically rich sentences of the TIMIT database ( Lamel et al. 1986 ) .


A third problem arises with the approach to the semantics of QLFs that this notion of the relationship between QLF and RQLF encourages one to adopt : it is that taken by Alshawi and Crouch ( 1992 ) .


In ( Lin , 2004 ) , I present evidence from Mandarin Chinese that this analysis is on the right track .


Interaction between components is coordinated by the dialogue manager which uses the informationstate approach ( Larsson and Traum , 2000 ) .


Other molecular biology databases We also included several model organism databases or nomenclature databases in the construction of the dictionary , i.e. , mouse Mouse Genome Database ( MGD ) [ 18 ] , fly FlyBase [ 19 ] , yeast Saccharomyces Genome Database ( SGD ) [ 20 ] , rat -- Rat Genome Database ( RGD ) [ 21 ] , worm -- WormBase [ 22 ] , Human Nomenclature Database ( HUGO ) [ 23 ] , Online Mendelian Inheritance in Man ( OMIM ) [ 24 ] , and Enzyme Nomenclature Database ( ECNUM ) [ 25 , 26 ] .


There are many more distinctions which are conveyed by the conjunction of grammar codes and word qualifiers ( see Michiels , 1982 , for further details ) .


The most common way is to divide each half of the bitext into an equal number of segments and to align the segments so that each pair of segments Si and Ti are translations of each other ( Gale & Church , 1991 ; Melamed , 1996a ) .


Leech et al. , 1983 ) .


Langendoen ( 1975 ) proposes readjustment rules similar to those of Chomsky and Halle , but he claims that the readjustment of structure is part of the grammar , not part of the performance model .


financial news , we created a probabilistic CzechEnglish dictionary by running GIZA + + training ( translation models 1-4 , see Och and Ney ( 2000 ) ) on the training part of the English-Czech WSJ parallel corpus extended by the parallel corpus of entry/translation pairs from the manual dictionary .


In the field of machine learning research , incremental training has been employed in the work ( Cauwenberghs and Poggio , 2001 ; Shilton et al. , 2005 ) , but there is little work for tuning parameters of statistical machine translation .


In a log-linear parameterization , for example , a prior that penalizes feature strengths far from 1 can be used to do feature selection and avoid overfitting ( Chen and Rosenfeld , 1999 ) .


We report performance in terms of two metrics : ( 1 ) the Fmeasure score as computed by the commonly-used MUC scorer ( Vilain et al. , 1995 ) , and ( 2 ) the accuracy on the anaphoric references , computed as the fraction of anaphoric references correctly resolved .


A study of the query log of the AllTheWeb and Altavista search sites gives an idea of the relevance of the people search task : 11-17 % of the queries were composed of a person name with additional terms and 4 % were identified as person names ( Spink et al. , 2004 ) .


This was done because purely unsupervised techniques ( e.g. , Baum-Welch [ Baum and Petrie 1966 ] or Brill 's [ Brill 1995b ] ) enable regularities to be induced for word classes which contain many entries , exploiting the fact that individual words that belong to a POS class occur in different ambiguity patterns .


Future research should apply the work of Blunsom et al. ( 2008 ) and Blunsom and Osborne ( 2008 ) , who marginalize over derivations to find the most probable translation rather than the most probable derivation , to these multi-nonterminal grammars .


In informal experiments described elsewhere ( Melamed 1995 ) , I found that the G2 statistic suggested by Dunning ( 1993 ) slightly outperforms 02 .


porating these two KSs into our resolver : they can Following Soon et al. ( 2001 ) , we select as the aneach be represented as a constraint or as a feature , tecedent of each NP , NPS , the closest preceding NP and they can be applied to the resolver in isolation that is classified as coreferent with NPS .


Using the section labels , the HMM was trained using the HTK toolkit ( Young et al. , 2002 ) , which efficiently performs the forward-backward algorithm and BaumWelch estimation .


In this paper , we use TF-IDF ( a kind of augmented DF ) as a feature selection criterion , in order to ensure results are comparable with those in ( Yahyaoui , 2001 ) .


A variety of statistical methods were proposed over the recent years for learning to produce a full parse of free-text sentences ( e.g. , Bod ( 1992 ) , Magerman ( 1995 ) , Collins ( 1997 ) , Ratnaparkhi ( 1997 ) , and Sekine ( 1998 ) ) .


There is a rich literature on organization and lexical access of morphologically complex words where experiments have been conducted mainly for derivational suffixed words of English , Hebrew , Italian , French , Dutch , and few other languages ( Marslen-Wilson et al. , 2008 ; Frost et al. , 1997 ; Grainger , et al. , 1991 ; Drews and Zwitserlood , 1995 ) .


In the disambiguation of capitalized words , the most widespread method is POS tagging , which achieves about a 3 % error rate on the Brown corpus and a 5 % error rate on the WSJ corpus , as reported in Mikheev ( 2000 ) .


The problem with this approach is that any threshold is , to some extent , arbitrary , and there is evidence to suggest that , for some tasks , low counts are important ( Collins and Brooks , 1995 ) .


Zollmann and Vogel ( 2011 ) further labeled the SCFG rules with POS tags and unsupervised word classes .


Steganography is concerned with hiding information in some cover medium , by manipulating properties of the medium in such a way that the hidden information is not easily detectable by an observer ( Fridrich , 2009 ) .


We offer a theorem that highlights the broad applicability of these modeling techniques .4 If f ( input , output ) is a weighted regular relation , then the following statements are equivalent : ( 1 ) f is a joint probabilistic relation ; ( 2 ) f can be computed by a Markovian FST that halts with probability 1 ; ( 3 ) f can be expressed as a probabilistic regexp , i.e. , a regexp built up from atomic expressions a : b ( for a E E U -LCB- E -RCB- , b E A U -LCB- E -RCB- ) using concatenation , probabilistic union + p , and probabilistic closure * p. For defining conditional relations , a good regexp language is unknown to us , but they can be defined in several other ways : ( 1 ) via FSTs as in Fig. 1c , ( 2 ) by compilation of weighted rewrite rules ( Mohri and Sproat , 1996 ) , ( 3 ) by compilation of decision trees ( Sproat and Riley , 1996 ) , ( 4 ) as a relation that performs contextual left-to-right replacement of input substrings by a smaller conditional relation ( Gerdemann and van Noord , 1999 ) ,5 ( 5 ) by conditionalization of a joint relation as discussed below .


Word pairs containing polysemous words are expanded to concept pairs using GermaNet ( Kunze , 2004 ) , the German equivalent to WordNet , as a sense inventory for each word .


Using the initial target U-trees , source sentences and word alignment , we extract minimal GHKM translation rules7 in terms of frontier nodes ( Galley et al. , 2004 ) .


For example , while it is difficult to induce a grammar with raw text alone , the task is tractable when the syntactic analysis for each sentence is provided as a part of the training data ( Pereira and Schabes 1992 ) .


Our results are lower than those of full parsers , e.g. , Collins ( 1997 ) as might be expected since much less structural data , and no lexical data are being used .


Our work is more similar to NLG work that concentrates on structural constraints such as generative poetry ( Greene et al. , 2010 ) ( Colton et al. , 2012 ) ( Jiang and Zhou , 2008 ) or song lyrics ( Wu et al. , 2013 ) ( Ramakrishnan A et al. , 2009 ) , where specified meter or rhyme schemes are enforced .


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 .


The result holds for both the MaltParser ( Nivre 2008 ) and the Easy-First Parser ( Goldberg and Elhadad 2010 ) .


This system has been successfully tested with the development of plug-ins supporting instant messaging , distributed video encoding ( Hughes and Walkerdine , 2005 ) , distributed virtual worlds ( Hughes et al. , 2005 ) and digital library management ( Walkerdine and Rayson , 2004 ) .


In modern syntactic theories ( e.g. , lexical-functional grammar [ LFG ] [ Kaplan and Bresnan 1982 ; Bresnan 2001 ; Dalrymple 2001 ] , head-driven phrase structure grammar [ HPSG ] [ Pollard and Sag 1994 ] , tree-adjoining grammar [ TAG ] [ Joshi 1988 ] , and combinatory categorial grammar [ CCG ] [ Ades and Steedman 1982 ] ) , the lexicon is the central repository for much morphological , syntactic , and semantic information .


We then use Illinois Chunker ( Punyakanok and Roth , 2001 ) 6 to extract more noun phrases from the text and employ Collins head rules ( Collins , 1999 ) to identify their heads .


Butt ( 1993 ) argues CV formations in Hindi and Urdu are either morphological or syntactical and their formation take place at the argument structure .


feature Cohen 's k corrected k agreement 73.59 98.74 dial act 84.53 98.87 turn 73.52 99.16 Table 2 : Inter-coder agreement on feedback expression annotation Although researchers do not totally agree on how to measure agreement in various types of annotated data and on how to interpret the resulting figures , see Artstein and Poesio ( 2008 ) , it is usually assumed that Cohen 's kappa figures over 60 are good while those over 75 are excellent ( Fleiss , 1971 ) .


Collins 1996 , Charniak 1997 , Collins 1999 and Charniak 2000 ) .


Two formalizations of lexical rules as used by HPSG linguists have been proposed , the meta-level lexical rules ( MLRs ; Calcagno 1995 ; Calcagno and Pollard 1995 ) and the .


We run TreeTagger ( Schmid , 1994 ) for tokenization , and used the Giza + + ( Och and Ney , 2003 ) to align the tokenized corpora at the word level .


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 ) .


We then go on to compare the current approach with that of some other theories with similar aims : the `` standard '' version of quasi-logical form implemented in the Core Language Engine , as rationally reconstructed by Alshawi and Crouch ( 1992 ) and Crouch and Pulman ( 1994 ) ; underspecified Discourse Representation Theory ( Reyle 1993 ) ; and the `` glue language '' approach of Dalrymple et al. ( 1996 ) .


Note that this ensures that greater importance is attributed to longer chunks , as is usual in most EBMT systems ( cfXXX Sato and Nagao 1990 ; Veale and Way 1997 ; Carl 1999 ) .7 As an example , consider the translation into French of the house collapsed .


Using WordNet , annotating the sem feature of an adjective involves first choosing the correct sense for the adjective 2Some descriptions of int modifiers can be found in ( Cheng and Mellish , 2000b ) .


One common approach is using Machine Translation ( MT ) to translate the queries to the language of the documents or translate documents to the language of the queries ( Gey et al , 1999 ; Oard , 1998 ) .


Adding selectional restrictions ( semantic feature information , Hobbs 1977 ) does not solve the problem , because isolated features offer only part of the background knowledge necessary for reference disambiguation .


Software engineering research on Generative Programming ( Czarnecki and Eisenecker , 2000 ) attempts to solve these problems by focusing on the development of configurable elementary components and knowledge to combine these components into complete systems .


Both use the evaluation software and triple encoding presented in Crouch et al. ( 2002 ) .


In this Section , we will describe some example cases , which are drawn from the problem of using synchronous formalisms to define translations between languages ( e.g. Shieber ( 1994 ) cases ) .


Some examples include text categorization ( Lewis and Catlett 1994 ) , base noun phrase chunking ( Ngai and Yarowsky 2000 ) , part-of-speech tagging ( Engelson Dagan 1996 ) , spelling confusion set disambiguation ( Banko and Brill 2001 ) , and word sense disambiguation ( Fujii et al. 1998 ) .


Most coreference resolution work simply mentions it in passing as a module in the pipelined system ( Chang et al. , 2013 ; Durrett and Klein , 2013 ; Lee et al. , 2011 ; Bj Â¨ orkelund and Kuhn , 2014 ) .


Because the judges do not evaluate the same cases , we could not employ standard inter-annotator agreement measures ( Carletta 1996 ) .


Related are also the studies by Rieks op den Akker and Schulz ( 2008 ) and Murray and Renals ( 2008 ) : both achieve promising results in the automatic segmentation of dialogue acts using the annotations in a large multimodal corpus .


Due to advances in statistical syntactic parsing techniques ( Collins , 1997 ; Charniak , 2001 ) , attention has recently shifted towards the harder question of analyzing the meaning of natural language sentences .


The reader may consult recent papers on this subject ( e.g. Moens and Steedman 1987 ; Webber 1987 ) to see what a formal interpretation of events in time might look like .


Because it is also consistent , it will be chosen as a best interpretation of S , ( cfXXX Zadrozny 1987a , 1987b ) .


For our experiments we used the standard division of the WSJ ( Marcus et al. 1993 ) , with sections 2 through 21 for training ( approx .


With respect to this , we apply the different priming and other lexical decision experiments , described in literature ( Marslen-Wilson et al. , 1994 ; Bentin , S. and Feldman , 1990 ) specifically for derivationally suffixed polymorphemic words and compound verbs of Bangla .


From this description , it should be clear that TM systems do not translate : Indeed , some researchers consider them to be little more than a search-and-replace engine , albeit a rather sophisticated one ( Macklovitch and Russell 2000 ) .


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 ) .


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 ) .


There are several variations of such a method ( Ballesteros and Croft , 1998 ; Pirkola , 1998 ; Hull 1997 ) .


This evaluation set-up is an improvement versus the one we previously reported ( Gerber and Chai 2010 ) , in which fixed partitions were used for training , development , and testing .


Saggion ( 2008 ) compared the performace of NEs versus BoW features .


The right-side context of a non-terminal category -- the probability of generating a category to the right of the current constituent 's category -- corresponds directly to the category transitions used for the HMM supertagger of Garrette et al. ( 2014 ) .


The starting point for the approach followed here was a dissatisfaction with certain aspects of the theory of quasi-logical form as described in Alshawi ( 1990 , 1992 ) , and implemented in SRI 's Core Language Engine ( CLE ) .


However , the method we are currently using in the ATIS domain ( Seneff et al. 1991 ) represents our most promising approach to this problem .


Three UniRef tables UniRef100 , UniRef90 and UniRef50 ) are available for download : UniRef100 combines identical sequences and sub-fragments into a single UniRef entry ; and UniRef90 and UniRef50 are built by clustering UniRef100 sequences into clusters based on the CD-HIT algorithm [ 16 ] such that each cluster is composed of sequences that have at least 90 % or 50 % sequence similarity , respectively , to the representative sequence .


Collins 1996 , Charniak 1997 , Collins 1999 and Charniak 2000 ) .


To name a few examples , Rohrbach et al. ( 2010 ) and Socher et al. ( 2013 ) show how semantic information from text can be used to improve zero-shot classification ( i.e. , classifying never-before-seen objects ) , and Motwani and Mooney ( 2012 ) show that verb clusters can be used to improve activity recognition in videos .


The computational treatment of lexical rules as covariation in lexical entries was implemented in Prolog by the authors in cooperation with Dieter Martini for the ConTroll system ( Gerdemann and King 1994 ; Gotz and Meurers 1997a ) .


Arabic has two kinds of plurals : broken plurals and sound plurals ( Wightwick and Gaafar , 1998 ; Chen and Gey , 2002 ) .


Although there are other discussions of the paragraph as a central element of discourse ( e.g. Chafe 1979 , Halliday and Hasan 1976 , Longacre 1979 , Haberlandt et al. 1980 ) , all of them share a certain limitation in their formal techniques for analyzing paragraph structure .


To prove that our method is effective , we also make a comparison between the performances of our system and Xue and Palmer ( 2005 ) , Xue ( 2008 ) .


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 ) .


Our plan is to implement a windowed or moving-average version of BLEU as in ( Chiang et al. , 2008 ) .


As Church ( 1988 ) rightly pointed out , however , `` Proper nouns and capitalized words are particularly problematic : some capitalized words are proper nouns and some are not .


The recent great advances in speech and language technologies have made it possible to build fully implemented spoken dialogue systems ( Aust et al. , 1995 ; Allen et al. , 1996 ; Zue et al. , 2000 ; Walker et al. , 2000 ) .


For instance , part of the ACE Phase 2 also adopted a corpus-based approach to SC deterevaluation involves classifying an NP as PERSON , mination that is investigated as part of the mention ORGANIZATION , GPE ( a geographical-political redetection ( MD ) task ( e.g. , Florian et al. ( 2006 ) ) .


In most cases , the accuracy of parsers degrades when run on out-of-domain data ( Gildea , 2001 ; McClosky et al. , 2006 ; Blitzer et al. , 2006 ; Petrov et al. , 2010 ) .


Based on this assumption , the problem of identifying mention heads is a sequential phrase identification problem , and we choose to employ the BILOU-representation as it has advantages over traditional BIO-representation , as shown , e.g. in Ratinov and Roth ( 2009 ) .


TF is given by TFD , t , and it denotes frequency of term t in document D. IDF is given by IDFt = log ( N/dft ) , where N is the number of documents in the collection , and dft is the number of documents containing the term t. ( Salton and Yang , 1973 ) proposed the combination of TF and IDF as weighting schemes , and it has been shown that their product gave better performance .


An HPSG grammar consists of lexical entries and ID grammar rules , each of which is described with typed feature structures ( Carpenter , 1992 ) .


More recently , Burke , Cahill , et al. ( 2004a ) carried out an evaluation of the automatic annotation algorithm against the publicly available PARC 700 Dependency Bank ( King et al. 2003 ) , a set of 700 randomly selected sentences from Section 23 which have been parsed , converted to dependency format , and manually corrected and extended by human validators .


In our work , we gather sets of sentences , and assume ( but do not employ ) existing approaches for their organization ( Goldstein et al. 2000 ; Barzilay , Elhadad , and McKeown 2001 ; Barzilay and McKeown 2005 ) .


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 ) .


This was done because purely unsupervised techniques ( e.g. , Baum-Welch [ Baum and Petrie 1966 ] or Brill 's [ Brill 1995b ] ) enable regularities to be induced for word classes which contain many entries , exploiting the fact that individual words that belong to a POS class occur in different ambiguity patterns .


Two formalizations of lexical rules as used by HPSG linguists have been proposed , the meta-level lexical rules ( MLRs ; Calcagno 1995 ; Calcagno and Pollard 1995 ) and the .


In terms of treebank data , the primary training corpus is the Penn Wall Street Journal Treebank ( PTB ) ( Marcus et al. , 1993 ) .


The extraction of each PICO element relies to a different extent on an annotated corpus of MEDLINE abstracts , created through an effort led by the first author at the National Library of Medicine ( Demner-Fushman et al. 2006 ) .


Various feature selection techniques have been used in automatic text categorization ; they include document frequency ( DF ) , information gain ( IG ) ( Tzeras and Hartman , 1993 ) , minimum description length principal ( Lang , 1995 ) , and the X2 statistic .


Usually , the classes are from WordNet ( Miller et al. , 1990 ) , although they can also be inferred from clustering ( Rooth et al. , 1999 ) .


The account sketched in Section 4 was superimposed on an incremental GRE algorithm , partly because incrementality is well established in this area ( Appelt 1985 ; Dale and Reiter 1995 ) .


Now for some important remarks on efficiency : â¢ Computing ti is an instance of the well-known algebraic path problem ( Lehmann , 1977 ; Tar an , 1981a ) .


Johns and Jones ( 2012 ) take an entirely different approach by showing that one can successfully infer held out feature norms from weighted mixtures based on textual similarity .


Over the last decade there has been a lot of interest in developing tutorial dialogue systems that understand student explanations ( Jordan et al. , 2006 ; Graesser et al. , 1999 ; Aleven et al. , 2001 ; Buckley and Wolska , 2007 ; Nielsen et al. , 2008 ; VanLehn et al. , 2007 ) , because high percentages of selfexplanation and student contentful talk are known to be correlated with better learning in humanhuman tutoring ( Chi et al. , 1994 ; Litman et al. , 2009 ; Purandare and Litman , 2008 ; Steinhauser et al. , 2007 ) .


Previous work in sentence planning in the natural language generation ( NLG ) community uses hand-written rules to approximate the distribution of linguistic phenomena in a corpus ( see ( Shaw , 1998 ) for a recent example with further references ) .


We assume that every determiner has its own equivalence , which resolves it as a quantifier : sometimes this can be quite a complicated matter , as with any ( Alshawi 1990 ) , which will resolve in different ways depending on its linguistic context , but here we avoid this complexity ' 6 Separate equivalences might also make it easier to encode determiner-specific preferences , such as that of each for wide scope .


Following Pinkal ( 1979 ) , such expressions will be called vague descriptions even though , as we shall see , the vagueness of the adjective does not extend to the description as a whole .


Such approaches have been tried recently in restricted cases ( McCallum et al. , 2000 ; Eisner , 2001b ; Lafferty et al. , 2001 ) .


The standard way to handle this problem is to handcraft a finite set of features which provides a sufficient summary of the unbounded history ( Ratnaparkhi , 1999 ; Collins , 1999 ; Charniak , 2000 ) .


Following Andrews et al. ( 2009 ) , we measure association norm prediction as an average of percentile ranks .


There is a general consensus among theoretical linguists that the proper representation of verbal argument structure is event structure -- representations grounded in a theory of events that decompose semantic roles in terms of primitive predicates representing concepts such as causality and inchoativity ( Dowty , 1979 ; Jackendoff , 1983 ; Pustejovsky , 1991b ; Rappaport Hovav and Levin , 1998 ) .


Other molecular biology databases We also included several model organism databases or nomenclature databases in the construction of the dictionary , i.e. , mouse Mouse Genome Database ( MGD ) [ 18 ] , fly FlyBase [ 19 ] , yeast Saccharomyces Genome Database ( SGD ) [ 20 ] , rat -- Rat Genome Database ( RGD ) [ 21 ] , worm -- WormBase [ 22 ] , Human Nomenclature Database ( HUGO ) [ 23 ] , Online Mendelian Inheritance in Man ( OMIM ) [ 24 ] , and Enzyme Nomenclature Database ( ECNUM ) [ 25 , 26 ] .


Liu et al. ( 2012 ) re-trained the linguistic parsers bilingually based on word alignment .


de URL : http://www.sfs.nphil.uni-tuebingen.de/sfb / b4home.html 1 This is , for example , the case for all proposals working with verbal lexical entries that raise the arguments of a verbal complement ( Hinrichs and Nakazawa 1989 ) that also use lexical rules such as the Complement Extraction Lexical Rule ( Pollard and Sag 1994 ) or the Complement Cliticization Lexical Rule ( Miller and Sag 1993 ) to operate on those raised elements .


Much of theoretical linguistics can be formulated in a very natural manner as stating correspondences ( translations ) between layers of representation structures ( Rambow & Satta , 1996 ) , such as the relation between syntax and semantic .


From an IR view , a lot of specialized research has already been carried out for medical applications , with emphasis on the lexico-semantic aspects of dederivation and decomposition ( Pacak et al. , 1980 ; Norton and Pacak , 1983 ; Wolff , 1984 ; Wingert , 1985 ; Dujols et al. , 1991 ; Baud et al. , 1998 ) .


The following are the various tag sets we use in this article : ( a ) the core POS tag sets CORE44 and the newly introduced CORE12 ; ( b ) CATiB Treebank tag set ( CATIB6 ) ( Habash and Roth 2009 ) and its newly introduced extension of CATIBEX created using simple regular expressions on word form , indicating particular morphemes such as the prefix JI Al + or the suffix v ' + wn ; this tag set is the best-performing tag set for Arabic on predicted values as reported in Section 4 ; ( c ) the PATB full tag set with complete morphological tag ( BW ) ( Buckwalter 2004 ) ; and two extensions of the PATB reduced tag set ( PENN POS , a.k.a. RTS , size 24 [ Diab , Hacioglu , and Jurafsky 2004 ] ) , both outperforming it : ( d ) Kulick , Gabbard , and Marcus ( 2006 ) 's tag set ( KULICK ) , size 43 , one of whose most important extensions is the marking of the definite article clitic , and ( e ) Diab and Benajiba 's ( in preparation ) EXTENDED RTS tag set ( ERTS ) , which marks gender , number , and definiteness , size 134 .


A similar problem is discussed in the psycholinguistics of interpretation ( Sedivy et al. 1999 ) : Interpretation is widely assumed to proceed incrementally , but vague descriptions resist strict incrementality , since an adjective in a vague description can only be fully interpreted when its comparison set is known .


In this paper , we evaluated the role of low-level image features , SURF and GIST , for their compatibility with the multimodal Latent Dirichlet Allocation model of Andrews et al. ( 2009 ) .


Figure 2 illustrates a DSyntS from a meteorological application , MeteoCogent ( Kittredge and Lavoie , 1998 ) , represented using the standard graphical notation and also the RealPro ASCII notation used internally in the framework ( Lavoie and Rambow , 1997 ) .


And Collins ( 2000 ) argues for `` keeping track of counts of arbitrary fragments within parse trees '' , which has indeed been carried out in Collins and Duffy ( 2002 ) who use exactly the same set of ( all ) tree fragments as proposed in Bod ( 1992 ) .


Boutsis and Piperidis ( 1998 ) use a tagged parallel corpus to extract translationally equivalent English-Greek clauses on the basis of word occurrence and co-occurrence probabilities .


The key linguistic knowledge sources that we use are morphological analysis and generation of German based on SMOR , a morphological analyzer/generator of German ( Schmid et al. , 2004 ) and the BitPar parser , which is a state-of-the-art parser of German ( Schmid , 2004 ) .


A common computational treatment of lexical rules adopted , for example , in the ALE system ( Carpenter and Penn 1994 ) consists of computing the transitive closure of the base lexical entries under lexical rule application at compile-time .


Manually defined heuristics are used to automatically annotate each tree in the treebank with partially specified HPSG derivation trees : Head/argument/modifier distinctions are made for each node in the tree based on Magerman ( 1994 ) and Collins ( 1997 ) ;


Authors may choose this right with the No-Deriv option of the Creative Commons licences ( Lessig , 2004 ) .


Mathematical analysis can assess a measure with respect to some formal properties , e.g. whether a measure is a metric ( Lin , 1998 ) .4 However , mathematical analysis can not tell us whether a measure closely resembles human judgments or whether it performs best when used in a certain application .


The same annotation scheme as in our previous work on anger detection has been applied , see e.g. ( Schmitt et al. , 2009 ) .


We also compute GIST vectors ( Oliva and Torralba , 2001 ) for every image using LearGIST ( Douze et al. , 2009 ) .


In modern syntactic theories ( e.g. , lexical-functional grammar [ LFG ] [ Kaplan and Bresnan 1982 ; Bresnan 2001 ; Dalrymple 2001 ] , head-driven phrase structure grammar [ HPSG ] [ Pollard and Sag 1994 ] , tree-adjoining grammar [ TAG ] [ Joshi 1988 ] , and combinatory categorial grammar [ CCG ] [ Ades and Steedman 1982 ] ) , the lexicon is the central repository for much morphological , syntactic , and semantic information .


The analysis of the data we have collected indicates that student satisfaction may be affected if the system rephrases student answers using different words ( for example , using better terminology ) but does n't explicitly explain the reason why different terminology is needed ( Dzikovska et al. , 2010 ) .


A logic that provides the formal architecture required by Pollard and Sag ( 1994 ) was defined by King ( 1989 , 1994 ) .


fields generally follow the pattern of `` introduction '' , `` methods '' , `` results '' , and `` conclusions '' ( SalangerMeyer , 1990 ; Swales , 1990 ; OrËasan , 2001 ) .


Collins et al. ( 1999 ) report that an optimal tag set for parsing Czech consists of a basic POS tag plus a CASE feature ( when applicable ) .


The elimination of redundant nondeterminism is based on Unfold/Fold transformation techniques ( Tamaki and Sato 1984 ) .29 The unfolding transformation is also referred to as partial execution , for example , by Pereira and Shieber ( 1987 ) .


Over the last decade there has been a lot of interest in developing tutorial dialogue systems that understand student explanations ( Jordan et al. , 2006 ; Graesser et al. , 1999 ; Aleven et al. , 2001 ; Buckley and Wolska , 2007 ; Nielsen et al. , 2008 ; VanLehn et al. , 2007 ) , because high percentages of selfexplanation and student contentful talk are known to be correlated with better learning in humanhuman tutoring ( Chi et al. , 1994 ; Litman et al. , 2009 ; Purandare and Litman , 2008 ; Steinhauser et al. , 2007 ) .


9 We do not relate to specific results in their study because it has been brought to our attention that Hohensee and Bender ( 2012 ) are in the process of rechecking their code for errors , and rerunning their experiments ( personal communication ) .


Inspired by ( Klein and Manning , 2003 ) , we split one phrase type into several subsymbols , which contain category information of current constituent 's parent .


The recent great advances in speech and language technologies have made it possible to build fully implemented spoken dialogue systems ( Aust et al. , 1995 ; Allen et al. , 1996 ; Zue et al. , 2000 ; Walker et al. , 2000 ) .


Moreover , in order to determine whether the performances of the predictive criteria are consistent across different learning models within the same domain , we have performed the study on two parsing models : one based on a context-free variant of tree-adjoining grammars ( Joshi , Levy , and Takahashi 1975 ) , the Probabilistic Lexicalized Tree Insertion Grammar ( PLTIG ) formalism ( Schabes and Waters 1993 ; Hwa 1998 ) , and Collins 's Model 2 parser ( 1997 ) .


Most of the early work on automatic f-structure annotation ( e.g. , van Genabith , Way , and Sadler 1999 ; Frank 2000 ; Sadler , van Genabith , and Way 2000 ) was applied only to small data sets ( fewer than 200 sentences ) and was largely proof of concept .


We prepare the training data by splitting compounds in two steps , following the technique of Fritzinger and Fraser ( 2010 ) .


Recent work by Korhonen ( 2002 ) on the filtering phase of this approach uses linguistic verb classes ( based on Levin [ 1993 ] ) for obtaining more accurate back-off estimates for hypothesis selection .


Numerous previous pseudodisambiguation evaluations only include arguments that occur between 30 and 3000 times ( Erk , 2007 ; Keller and Lapata , 2003 ; Rooth et al. , 1999 ) .


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 ) .


Default parameters were used , although experimentation with different parameter settings is an important direction for future work ( Daelemans and Hoste , 2002 ; Munson et al. , 2005 ) .


The language chosen for semantic representation is a flat semantics along the line of ( Bos , 1995 ; Copestake et al. , 1999 ; Copestake et al. , 2001 ) .


For example , Jokinen and Ragni ( 2007 ) and Jokinen et al. ( 2008 ) find that machine learning algorithms can be trained to recognise some of the functions of head movements , while Reidsma et al. ( 2009 ) show that there is a dependence between focus of attention and assignment of dialogue act labels .


As a logical postulate it is not very radical ; it is possible within a finitary framework to develop that part of mathematics that is used or has potential applications in natural science , such as mathematical analysis ( cfXXX Mycielski 1981 ) .


In a similar vain to Skut and Brants ( 1998 ) and Buchholz et al. ( 1999 ) , the method extends an existing flat shallow-parsing method to handle composite structures .


An interesting aspect of our generative approach is that we model HMM outputs as Gaussian vectors ( log probabilities of observing entire sentences based on our language models ) , as opposed to sequences of terms , as done in ( Barzilay and Lee , 2004 ) .


â¢ language learning ( Green 1979 ; Mori and Moeser 1983 ; Morgan , Meier , and Newport 1989 ) â¢ monolingual grammar induction ( Juola 1998 ) â¢ grammar optimization ( Juola 1994 ) â¢ insights into universal grammar ( Juola 1998 ) â¢ machine translation ( Juola 1994 , 1997 ; Veale and Way 1997 ; Gough , Way , and Hearne 2002 )


In Charniak ( 1996 ) and Krotov et al. ( 1998 ) , it was observed that treebank grammars ( CFGs extracted from treebanks ) are very large and grow with the size of the treebank .


We apply our system to the latest version of the XTAG English grammar ( The XTAG Research Group , 2001 ) , which is a large-scale FB-LTAG grammar .


Furthermore , the need to answer questions related to patient care at the point of service has been well studied and documented ( Covell , Uman , and Manning 1985 ; Gorman , Ash , and Wykoff 1994 ; Ely et al. 1999 , 2005 ) .


Typical examples are Bulgarian ( Simov et al. , 2005 ; Simov and Osenova , 2003 ) , Chinese ( Chen et al. , 2003 ) , Danish ( Kromann , 2003 ) , and Swedish ( Nilsson et al. , 2005 ) .


Over the last decade there has been a lot of interest in developing tutorial dialogue systems that understand student explanations ( Jordan et al. , 2006 ; Graesser et al. , 1999 ; Aleven et al. , 2001 ; Buckley and Wolska , 2007 ; Nielsen et al. , 2008 ; VanLehn et al. , 2007 ) , because high percentages of selfexplanation and student contentful talk are known to be correlated with better learning in humanhuman tutoring ( Chi et al. , 1994 ; Litman et al. , 2009 ; Purandare and Litman , 2008 ; Steinhauser et al. , 2007 ) .


Worst case , calculating the set corresponding with such a property , of the form size ( x ) = maxm , for example , involves sorting the distractors as to their size , which may amount to O ( n2d ) or O ( nd log nd ) calculations ( depending on the sorting algorithm : cfXXX [ Aho et al. 1983 ] Chapter 8 ) .


Virpioja et al. ( 2007 ) , Badr et al. ( 2008 ) , Luong et al. ( 2010 ) , Clifton and Sarkar ( 2011 ) , and others are primarily concerned with using morpheme segmentation in SMT , which is a useful approach for dealing with issues of word-formation .


While corpus driven efforts along the PARSEVAL lines ( Black et al. , 1991 ) are good at giving some measure of a grammar coverage , they are not suitable for finer grained analysis and in particular , for progress evaluation , regression testing and comparative report generation .


Before using the DCA method , we applied a Russian morphological processor ( Mikheev and Liubushkina 1995 ) to convert each word in the text to its main form : nominative case singular for nouns and adjectives , infinitive for verbs , etc. .


The result holds for both the MaltParser ( Nivre 2008 ) and the Easy-First Parser ( Goldberg and Elhadad 2010 ) .


Also relevant is work on the general problems of dialog-act tagging ( Stolcke et al. , 2000 ) , citation analysis ( Lehnert et al. , 1990 ) , and computational rhetorical analysis ( Marcu , 2000 ; Teufel and Moens , 2002 ) .


The language chosen for semantic representation is a flat semantics along the line of ( Bos , 1995 ; Copestake et al. , 1999 ; Copestake et al. , 2001 ) .


In simple terms , P2P is a technology that takes advantage of the resources and services available at the edge of the Internet ( Shirky , 2001 ) .


A common way to combine different models consists of selecting the model that is most confident regarding its decision ( Burke 2002 ) .


Common sense ( as well as the Gricean maxims ; Grice 1975 ) suggests that vague descriptions are preferred by speakers over quantitative ones whenever the additional information provided by a quantitative description is irrelevant to the purpose of the communication .


A similar method is included in PATR-II ( Shieber et al. 1983 ) and can be used to encode lexical rules as binary relations in the CUF system ( Dorre and Eisele 1991 ; Done and Dorna 1993b ) or the TFS system ( Emele and Zajac 1990 ; Emele 1994 ) .


For automatically extracting these surface level mappings we will draw on the approach to learning paraphrases from a corpus that is described in Barzilay and McKeown ( 2001 ) .


This description can then be given the standard set-theoretical interpretation of King ( 1989 , 1994 ) . '


Griffiths et al. ( 2007 ) helped pave the path for cognitive-linguistic multimodal research , showing that Latent Dirichlet Allocation outperformed Latent Semantic Analysis ( Deerwester et al. , 1990 ) in the prediction of association norms .


A more flexible approach is used by Reiter and Sripada ( 2002 ) , where users can specify boundary values for attributes like rainfall , specifying , for example , rain counts as moderate above 7 mm/h , as heavy above 20 mm/h , and so on .


Collins and Duffy ( 2002 ) define a kernel over parse trees and apply it to re-ranking the output of a parser , but the resulting feature space is restricted by the need to compute the kernel efficiently , and the results are not as good as Collins ' previous work on re-ranking using a finite set of features ( Collins , 2000 ) .


The shallow parser used is the SNoW-based CSCL parser ( Punyakanok and Roth , 2001 ; Munoz et al. , 1999 ) .


In practice , perceptron-type algorithms are often applied in a batch learning scenario , i.e. , the algorithm is applied for K epochs to a training sample of size T and then used for prediction on an unseen test set ( Freund and Schapire , 1999 ; Collins , 2002 ) .


Table 2 shows the results on identifying all phrases -- chunking in CoNLL2000 ( Tjong Kim Sang and Buchholz , 2000 ) terminology .


Unfortunately , as shown in ( Okanohara and Tsujii , 2007 ) , with the represetation of sentences that we use , linear classifiers can not discriminate real sentences from sentences sampled from a trigram , which is the model we use as a baseline , so here we resort to a non-linear large-margin classifier ( see section 3 for details ) .


Perhaps some variation of multi-level bulleted lists , appropriately integrated with interface elements for expanding and hiding items , might provide physicians a better overview of the information landscape ; see , for example , Demner-Fushman and Lin ( 2006 ) .


Pierce and Cardie ( 2001 ) have shown , in the context of base noun identification , that combining sample selection and cotraining can be an effective learning framework for large-scale training .