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The importance of including nonheadwords has become uncontroversial ( e.g. Collins 1999 ; Charniak 2000 ; Goodman 1998 ) .

Some methods of semantic relation analysis rely on predefined templates filled with information from processed texts ( Baker et al. , 1998 ) .

The example used to illustrate the power of ATNs ( Woods 1986 ) , `` John was believed to have been shot , '' also parses correctly , because the [ object ] node following the verb `` believed '' acts as both an absorber and a ( re ) generator .

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 ) .

LiLFeS is one of the fastest inference engines for processing feature structure logic , and efficient HPSG parsers have already been built on this system ( Nishida et al. , 1999 ; Torisawa et al. , 2000 ) .

As in ( Lee et al. , 2003 ) , we used unsupervised training data which is automatically segmented to discover previously unseen stems .

To address this limitation , our previous work ( Zhang and Chai , 2009 ) has initiated an investigation on the problem of conversation entailment .

∗ A brief version of this work , with some additional material , first appeared as ( Eisner , 2001a ) .

They also proposed two major categories of meta-learning approaches for recommender systems , merging and ensemble , each subdivided into the more specific subclasses suggested by Burke ( 2002 ) as follows .

Here , I adopt the model proposed by Marantz ( 1997 ) and decompose lexical verbs into verbalizing heads and verbal roots .

This heuristic is called soft union ( DeNero and Klein 2007 ) .

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 ) .

Many investigators ( e.g. Allen 1976 ; Elowitz et al. 1976 ; Luce et al. 1983 ; Cahn 1988 ) have suggested that the poor prosody of synthetic speech , in comparison with natural speech , is the primary factor leading to difficulties in the comprehension of fluent synthetic speech .

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 .

This semantics was constructed ( Zadrozny 1987a , 1987b ) as a formal framework for default and commonsense reasoning .

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 ) .

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 ) .

The EDR has close ties to the named entity recognition ( NER ) and coreference resolution tasks , which have been the focus of several recent investigations ( Bikel et al. , 1997 ; Miller et al. , 1998 ; Borthwick , 1999 ; Mikheev et al. , 1999 ; Soon et al. , 2001 ; Ng and Cardie , 2002 ; Florian et al. , 2004 ) , and have been at the center of evaluations such as : MUC-6 , MUC-7 , and the CoNLL '02 and CoNLL '03 shared tasks .

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

R98 ( , , , , „ ) uses a variant of Kozima 's semantic similarity measure ( Kozima , 1993 ) to compute block similarity .

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 .

We used a publicly available tagger ( Ratnaparkhi , 1996 ) to tag the words and then used these in the input to the system .

Some works abstract perception via the usage of symbolic logic representations ( Chen et al. , 2010 ; Chen and Mooney , 2011 ; Matuszek et al. , 2012 ; Artzi and Zettlemoyer , 2013 ) , while others choose to employ concepts elicited from psycholinguistic and cognition studies .

Multilingual lexical databases aligned with the English WordNet ( e.g. MultiWordNet ( Pianta et al. , 2002 ) ) have been created for several languages , with different degrees of coverage .

An off-the-shelf speech recognition device , a Nippon Electric Corporation DP-200 , was added to an existing natural language processing system , the Natural Language Computer ( NLC ) ( Ballard 1979 , Biermann and Ballard 1980 ) .

For future work , we might investigate how machine learning algorithms , which are specifically designed for the problem of domain adaptation ( Blitzer et al. , 2007 ; Jiang and Zhai , 2007 ) , perform in comparison to our approach .

But their importance has grown far beyond machine translation : for instance , transferring annotations between languages ( Yarowsky and Ngai 2001 ; Hwa et al. 2005 ; Ganchev , Gillenwater , and Taskar 2009 ) ; discovery of paraphrases ( Bannard and Callison-Burch 2005 ) ; and joint unsupervised POS and parser induction across languages ( Snyder and Barzilay 2008 ) .

That is , if the current hypothesis is unable to label a candidate or is uncertain about it , then the candidate might be a good training example ( Lewis and Catlett 1994 ) .

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 ) .

For instance , the derived morphological forms are believed to be represented as a whole , whereas the representation of the inflected forms follows the morphemic model ( Caramazza et al. , 1988 ) .

We perceive that these results can be extended to other language models that properly embed bilexical context-free grammars , as for instance the more general history-based models used in ( Ratnaparkhi , 1997 ) and ( Chelba and Jelinek , 1998 ) .

Another paper ( Yoshinaga et al. , 2001 ) describes the detailed analysis on the factor of the difference of parsing performance .

The original and the obtained grammar generated exactly the same number of derivation trees in the parsing experiment with 457 sentences from the ATIS corpus ( Marcus et al. , 1994 ) 6 ( the average length is 6.32 words ) .

The use of running tallies and percentages is based on the assumption that these features are likely to produce generalized predictors ( Litman et al. , 1999 ) .

The Longman lexicographers have developed a grammar coding system capable of representing in compact form a nontrivial amount of information , usually to be found only in large descriptive grammars of English ( such as Quirk et al. , 1985 ) .

19 The paper by Alkuhlani and Habash ( 2012 ) presents additional , more sophisticated models that we do not use in this article .

Empirical evidence has been brought forward that inflectional and/or derivational stemmers augmented by dictionaries indeed perform substantially better than those without access to such lexical repositories ( Krovetz , 1993 ; Kraaij and Pohlmann , 1996 ; Tzoukermann et al. , 1997 ) .

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 .

( Details of how the average-expert model performs can be found in our prior work ( Xiong and Litman , 2011 ) . )

Self-training should also benefit other discriminatively trained parsers with latent annotations ( Petrov and Klein , 2008 ) , although training would be much slower compared to using generative models , as in our case .

We introduce here a clearly defined and replicable split of the ACE 2004 data , so that future investigations can accurately and correctly compare against the results presented here .

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 ) .

Brent ( 1993 ) relies on morphosyntactic cues in the untagged Brown corpus as indicators of six predefined subcategorization frames .

To build the above s2t system , we first use the parse tree , which is generated by parsing the English side of the bilingual data with the Berkeley parser ( Petrov et al. , 2006 ) .

One obvious approach to this problem is to employ parser reranking ( Collins , 2000 ) .

Ideally , to distinguish between raising and equi verbs , a number of syntactic criteria should be employed ( Perlmutter and Soames , 1979:460 ff . )

The table also presents the closest comparable experimental results reported by McKnight and Srinivasan ( 2003 ) .1 McKnight and Srinivasan ( henceforth , M&S ) created a test collection consisting of 37,151 RCTs from approximately 12 million MEDLINE abstracts dated between 1976 and 2001 .

How this mismatched perceptual basis affects referential communication in situated dialogue was investigated in our previous work ( Liu et al. , 2012 ) .

Andrews et al. ( 2009 ) furthered this work by showing that a bimodal topic model , consisting of both text and feature norms , outperformed models using only one modality on the prediction of association norms , word substitution errors , and semantic interference tasks .

A cooccurrence based stemmer ( Xu and Croft , 1998 ) was used to stem Spanish words .

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 .

In a number of proposals , lexical generalizations are captured using lexical underspecification ( Kathol 1994 ; Krieger and Nerbonne 1992 ;

Although a grid may be more descriptively suitable for some aspects of prosody ( for example , Sproat and Liberman ( 1987 ) use the grid representation for their implementation of stress assignment in compound nominals ) , we are not aware of any evidence for or against a grid representation of discourseneutral phrasing .

The bottom panel of table 1 lists the results for the chosen lexicalized model ( SSN-Freq > 200 ) and five recent statistical parsers ( Ratnaparkhi , 1999 ; Collins , 1999 ; Charniak , 2000 ; Collins , 2000 ; Bod , 2001 ) .

Other factors , such as the role of focus ( Grosz 1977 , 1978 ; Sidner 1983 ) or quantifier scoping ( Webber 1983 ) must play a role , too .

linguistic in nature , rather than dealing with superficial properties of the text , e.g. the amount of white space between words ( Por et al. , 2008 ) .

The second version ( RM ) concerns the Resource Management task ( Pallett 1989 ) that has been popular within the DARPA community in recent years .

Another line of research that is correlated with ours is recognition of agreement/disagreement ( Misra and Walker , 2013 ; Yin et al. , 2012 ; Abbott et al. , 2011 ; Andreas et al. , 2012 ; Galley et al. , 2004 ; Hillard et al. , 2003 ) and classification of stances ( Walker et al. , 2012 ; Somasundaran and Wiebe , 2010 ) in online forums .

The studies presented by Goldwater and Griffiths ( 2007 ) and Johnson ( 2007 ) differed in the number of states that they used .

A number of alignment techniques have been proposed , varying from statistical methods ( Brown et al. , 1991 ; Gale and Church , 1991 ) to lexical methods ( Kay and Roscheisen , 1993 ; Chen , 1993 ) .

We would like to use features that look at wide context on the input side , which is inexpensive ( Jiampojamarn et al. , 2007 ) .

Much of the earlier work in anaphora resolution heavily exploited domain and linguistic knowledge ( Sidner 1979 ; Carter 1987 ; Rich and LuperFoy 1988 ; Carbonell and Brown 1988 ) , which was difficult both to represent and to process , and which required considerable human input .

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

This is then generalized , following a methodology based on Block ( 2000 ) , to generate the `` generalized marker lexicon . ''

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 ) .

Our proposed method is based on the automatically acquired paraphrase dictionary described in Callison-Burch ( 2008 ) , in which the application of paraphrases from the dictionary encodes secret bits .

For example , frequent words are translated less consistently than rare words ( Melamed , 1997 ) .

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 ) .

These knowledge sources were effectively used to build a state-of-the-art WSD program in one of our prior work ( Lee and Ng , 2002 ) .

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 ) .

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 .

This is where robust syntactic systems like SATZ ( Palmer and Hearst 1997 ) or the POS tagger reported in Mikheev ( 2000 ) , which do not heavily rely on word capitalization and are not sensitive to document length , have an advantage .

category relationships from the weak supervision : the tag dictionary and raw corpus ( Garrette and Baldridge , 2012 ; Garrette et al. , 2015 ) .4 This procedure attempts to automatically estimate the frequency of each word/tag combination by dividing the number of raw-corpus occurrences of each word in the dictionary evenly across all of its associated tags .

WIT has been implemented in Common Lisp and C on UNIX , and we have built several experimental and demonstration dialogue systems using it , including a meeting room reservation system ( Nakano et al. , 1999b ) , a video-recording programming system , a schedule management system ( Nakano et al. , 1999a ) , and a weather infomiation system ( Dohsaka et al. , 2000 ) .

Lexical functional grammar ( Kaplan and Bresnan 1982 ; Bresnan 2001 ; Dalrymple 2001 ) is a member of the family of constraint-based grammars .

Sarkar and Zeman ( 2000 ) present an approach to learn previously unknown frames for Czech from the Prague Dependency Bank ( Hajic

A companion paper describes the evaluation process and results in further detail ( Chu-Carroll and Nickerson , 2000 ) .

SNoW ( Carleson et al. , 1999 ; Roth , 1998 ) is a multi-class classifier that is specifically tailored for learning in domains in which the potential number of information sources ( features ) taking part in decisions is very large , of which NLP is a principal example .

Hence , enumerating morphological variants in a semi-automatically generated lexicon , such as proposed for French ( Zweigenbaum et al. , 2001 ) , turns out to be infeasible , at least for German and related languages .

It is analogous to the step in other translation model induction algorithms that sets all probabilities below a certain threshold to negligible values ( Brown et al. , 1990 ; Dagan et al. , 1993 ; Chen , 1996 ) .

They proved to be useful in a number of NLP applications such as natural language generation ( Iordanskaja et al. , 1991 ) , multidocument summarization ( McKeown et al. , 2002 ) , automatic evaluation of MT ( Denkowski and Lavie , 2010 ) , and TE ( Dinu and Wang , 2009 ) .

The results , which partly confirm those obtained on a smaller dataset in Paggio and Navarretta ( 2010 ) , must be seen in light of the fact that our gesture annotation scheme comprises more fine-grained categories than most of the studies mentioned earlier for both head movements and face expressions .

We employ the idea of ultraconservative update ( Crammer and Singer , 2003 ; Crammer et al. , 2006 ) to propose two incremental methods for local training in Algorithm 2 as follows .

It has also been shown to be useful in joint inference of text with visual attributes obtained using visual classifiers ( Silberer et al. , 2013 ) .

Gurevych ( 2006 ) reported a correlation of r = .69 .

A more subtle example is weighted FSAs that approximate PCFGs ( Nederhof , 2000 ; Mohri and Nederhof , 2001 ) , or to extend the idea , weighted FSTs that approximate joint or conditional synchronous PCFGs built for translation .

As has been previously observed and exploited in the NLP literature ( Pang and Lee , 2004 ; Agarwal and Bhattacharyya , 2005 ; Barzilay and Lapata , 2005 ) , the above optimization function , unlike many others that have been proposed for graph or set partitioning , can be solved exactly in an provably efficient manner via methods for finding minimum cuts in graphs .

WIT features an incremental understanding method ( Nakano et al. , 1999b ) that makes it possible to build a robust and real-time system .

This choice is inspired by recent work on learning syntactic categories ( Yatbaz et al. , 2012 ) , which successfully utilized such language models to represent word window contexts of target words .

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 ) .

Other studies which view lR as a query generation process include Maron and Kuhns , 1960 ; Hiemstra and Kraaij , 1999 ; Ponte and Croft , 1998 ; Miller et al , 1999 .

In Section 5 , we discuss the difficulties associated with such user studies , and describe a human-based evaluation we conducted for a small subset of the responses generated by our system ( Marom and Zukerman 2007b ) .

Hook ( 1981 ) considers the second verb V2 as an aspectual complex comparable to the auxiliaries .

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

In this situation , Brown et al. ( 1993b , 293 ) recommend `` evaluating the expectations using only a single , probable alignment . ''

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 ) .

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

Following our previous work on stance classification ( Hasan and Ng , 2013c ) , we employ three types of features computed based on the frame-semantic parse of each sentence in a post obtained from SEMAFOR ( Das et al. , 2010 ) .

However , the literature on Linguistic Steganography , in which linguistic properties of a text are modified to hide information , is small compared with other media ( Bergmair , 2007 ) .

This has been reported for other languages , too , dependent on the generality of the chosen approach ( J ¨ appinen and Niemist ¨ o , 1988 ; Choueka , 1990 ; Popovic and Willett , 1992 ; Ekmekc ¸ ioglu et al. , 1995 ; Hedlund et al. , 2001 ; Pirkola , 2001 ) .