hrithikpiyush/acl-arc huggingface dataset:
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 . Silberer and Lapata ( 2012 ) introduce a new method of multimodal integration based on Canonical Correlation Analysis , and performs a systematic comparison between their CCA-based model and others on association norm prediction , held out feature prediction , and word similarity . As computer vision techniques have improved over the past decade , other research has begun directly using visual information in place of feature norms .
Figure 8 gives an English-French transfer rule applied to a weather domain for the transfer of a verb modified by the adverb ALMOST : More details on how the structural divergences described in ( Don , 1994 ) can be accounted for using our formalism can be found in ( Nasr et al. , 1998 ) .
The tutorial policy makes a high-level decision as to which strategy to use ( for example , `` acknowledge the correct part and give a high specificity hint '' ) based on the answer analysis and dialogue context . At present , the system takes into consideration the number of incorrect answers received in response to the current question and the number of uninterpretable answers .1 In addition to a remediation policy , the tutorial planner implements an error recovery policy ( Dzikovska et al. , 2009 ) . Since the system accepts unrestricted input , interpretation errors are unavoidable .
However , precision is usually manually evaluated , so the figures are at least indicative for a comparison with previous work : One state-of-theart system introduced by Zhao et al. ( 2008 ) extracts paraphrase fragments from bilingual parallel corpora and reaches a precision of 0.67 . We found the same number using our previous approach ( Wang and Callison-Burch , 2011 ) , which is roughly equivalent to our core module . Our approach outperforms both by 17 % with similar estimated productivity .
But if big is applied to a person then it is far from clear that there is one canonical formula for mapping the different dimensions of your body into one overall dimension , and this complicates the situation . Similar things hold for multifaceted properties like intelligence ( Kamp 1975 ) . Color terms are a case apart .
In our experiment , intra-subject correlation was r = .670 for the first and r = .623 for the second individual who repeated the experiment , yielding a summarized intra-subject correlation of r = .647 . Rubenstein and Goodenough ( 1965 ) reported an intra-subject correlation of r = .85 for 15 subjects judging the similarity of a subset ( 36 ) of the original 65 word pairs . The values may again not be compared directly .
• Learnability ( Zernik and Dyer 1987 ) • Text generation ( Hovy 1988 ; Milosavljevic , Tulloch , and Dale 1996 ) • Speech generation ( Rayner and Carter 1997 ) • Localization ( Sch ¨ aler 1996 ) More recently , Simard and Langlais ( 2001 ) have proposed the exploitation of TMs at a subsentential level , while Carl , Way , and Sch ¨ aler ( 2002 ) and Sch ¨ aler , Way , and Carl ( 2003 , pages 108 -- 109 ) describe how phrasal lexicons might come to occupy a central place in a future hybrid integrated translation environment . This , they suggest , may result in a paradigm shift from TM to EBMT via the phrasal lexicon : Translators are on the whole wary of MT technology , but once subsentential alignment is enabled , translators will become aware of the benefits to be gained from ( source , target ) phrasal segments , and from there they suggest that `` it is a reasonably short step to enabling an automated solution via the recombination element of EBMT systems such as those described in [ Carl and Way 2003 ] . ''
Although the effectiveness and coverage of my parser remains to be seen , similar approaches have been successful at capturing complex linguistic phenomena . With a minimal set of features and a small number of lexical entries , Niyogi ( 2001 ) has successfully modeled many of the argument alternations described by Levin ( 1993 ) using a Hale and Keyser ( 1993 ) style analysis . I believe that with a suitable lexicon ( either hand crafted or automatically induced ) , my framework can be elaborated into a system whose performance is comparable to that of current statistical parsers , but with the added advantage of simultaneously providing a richer lexical semantic representation of the input sentence than flat predicate argument structures based on semantic roles .
What we said above has also disregarded elements of the `` global '' ( i.e. , not immediately available ) context . For some adjectives , including the ones that Bierwisch ( 1989 ) called evaluative ( as opposed to dimensional ) , this is clearly inadequate . He argued that evaluative adjectives ( such as beautiful and its antonym ugly ; smart and its antonym stupid , etc. ) can be recognized by the way in which they compare with antonyms .
$ Implementation 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 ) . The meeting room reservation system has vocabulary of about 140 words , around 40 phrase structure rules , nine attributes in the semantic frame , and around 100 speech files .
One is to adopt Pinkal 's `` radical underspecification '' approach ( Pirikal 1995 ) and use underspecified representations for all types of ambiguity , even syntactic ambiguity . The more conservative approach is to try to integrate existing statistical disambiguation schemes for QLFs , either individually or in a `` packed '' structure ( Alshawi and Carter 1994 ) , with the resolution process as described here . Alternatively , I believe it is worth exploring the approach to disambiguation described in Pulman ( 2000 ) , which would mesh nicely with the theory presented here .
Paraphrase tables ( PPHT ) contain pairs of corresponding phrases in the same language , possibly associated with probabilities . 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 ) . One of the proposed methods to extract paraphrases relies on a pivot-based approach using phrase alignments in a bilingual parallel corpus ( Bannard and Callison-Burch , 2005 ) .
Textual Entailment systems are given two textual fragments , text T and hypothesis H , and attempt to decide if the meaning of H can be inferred from the meaning of T ( Dagan et al. , 2005 ) . While many approaches have addressed this problem , our work is most closely related to that of ( Raina et al. , 2005 ; MacCartney and Manning , 2007 ; Tatu and Moldovan , 2006 ; Braz et al. , 2005 ) , which convert the inputs into logical forms and then attempt to ` prove ' H from T plus a set of axioms . For instance , ( Braz et al. , 2005 ) represents T , H , and a set of rewrite rules in a description logic framework , and determines entailment by solving an integer lin -
Furthermore , medical terminology is characterized by a typical mix of Latin and Greek roots with the corresponding host language ( e.g. , German ) , often referred to as neo-classical compounding ( McCray et al. , 1988 ) . While this is simply irrelevant for general-purpose morphological analyzers , dealing with such phenomena is crucial for any attempt to cope adequately with medical free-texts in an IR setting ( Wolff , 1984 ) . We here propose an approach to document retrieval which is based on the idea of segmenting query and document terms into basic subword units .
Unless Small Gaps and Dichotomy forbid it , we expected that preference should be given to the base form . In English , where the base form is morphologically simpler than the other two , this rule could be argued to follow from Gricean principles ( Grice 1975 ) . To keep matters simple , linguistic realization could choose the base form if and only if the gap between s − and s + surpasses a certain value , which is specified interactively by the user .
for which semantic information would be available . More generally , distributional clustering techniques ( Sch ¨ utze , 1992 ; Pereira et al. , 1993 ) could be applied to extract semantic classes from the corpus itself . Since the constraints on adjective ordering in English depend largely on semantic classes , the addition of semantic information to the model ought to improve the results .
Fung and McKeown ( 1997 ) attempt to translate technical terms using word relation matrices , although the resource from which such relations are derived is a pair of nonparallel corpora . Somers ( 1998 ) replicates the work of Fung and McKeown with different language pairs using the simpler metric of Levenshtein distance . 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 .
In this paper we investigate the selective application of magic to typed feature grammars a type of constraint-logic grammar based on Typed Feature Logic ( T r ; G6tz , 1995 ) . Typed feature grammars can be used as the basis for implementations of Head-driven Phrase Structure Grammar ( HPSG ; Pollard and Sag , 1994 ) as discussed in ( Gotz and Meurers , 1997a ) and ( Meurers and Minnen , 1997 ) . Typed feature grammar constraints that are inexpensive to resolve are dealt with using the top-down interpreter of the ConTroll grammar development system ( GOtz and Meurers , 1997b ) which uses an advanced search function , an advanced selection function and incorporates a coroutining mechanism which supports delayed interpretation .
These limitations reinforce the notion that automated responses should be assessed on their own merit , rather than with respect to some model response . In Marom and Zukerman ( 2007a ) we identified several systems that resemble ours in that they provide answers to queries . These systems addressed the evaluation issue as follows .
This list includes common words for a given language , but no supplementary information such as POS or morphological information is required to be present in this list . A variety of such lists for many languages are already available ( e.g. , Burnage 1990 ) . Words in such lists are usually supplemented with morphological and POS information ( which is not required by our method ) .
If the usefulness of NLG resides in its ability to present data in human-accessible form , then vagueness must surely be one of its central instruments , because it allows the suppression of irrelevant detail . In principle , this might be done by providing the generator with vague input -- in which case no special algorithms are needed -- but suitably contextualized vague input is often not available ( Mellish 2000 ) . The only practical alternative is to provide the generator with `` crisp '' ( i.e. , quantitative ) input , allowing the generator to be hooked on to a general-purpose database .
For each kind of evaluation , we have found one case where we can come close . We induced a two-class word-to-word model of translational equivalence from 13 million words of the Canadian Hansards , aligned using the method in ( Gale & Church , 1991 ) . One class represented content-word links and the other represented function-word links4 .
Accomplishments and achievements both express a change of state , and hence are temporally bounded ( telic ) ; achievements are punctual , whereas accomplishments extend over a period of time . Tenny ( 1987 ) observes that accomplishments differ from achievements only in terms of event duration , which is often a question of granularity . From typological studies , it appears that states , change of states , and activities form the most basic ontology of event types .
The resulting speech understanding system is called the Voice Natural Language Computer with Expectation ( VNLCE , Fink 1983 ) . [ The current system should be distinguished from an earlier voice system ( VNLC , Biermann et al. 1985 ) , which had no expectation and which handled discrete speech where a 300 millisecond pause must follow each word . ] It should be emphasized , of course , that the central issue here is the study of expectation mechanisms and the details of the design decisions could have been made in rather different ways .
The first chronicled endeavour to connect text elements and organise connections between them goes back to the 51h century B.C. and the work of Paninil . He was a grammarian who analysed Sanskrit ( Misra , 1966 ) . The idea resurfaced forcefully at several points in the more recent history of linguistic research ( Tesni`ere , 1959 ; Gruber , 1965 ; Fillmore , 1968 ) .
Of the remaining citations , 275 were used for training and rule derivation , as described in the following sections . After much exploration , Demner-Fushman et al. ( 2006 ) discovered that it was not practical to annotate PICO entities at the phrase level due to significant unresolvable disagreement and interannotator reliability issues . Consider the following segment : This double-blind , placebo-controlled , randomized , 3-period , complete block , 6-week crossover study examined the efficacy of simvastatin in adult men and women ( N = 151 ) with stable type 2 DM , low density lipoprotein-cholesterol 100 mg/dL , HDL-C < 40 mg/dL , and fasting triglyceride level > 150 and < 700 mg/dL .
We use a standard split of 268 training documents , 68 development documents , and 106 testing documents ( Culotta et al. , 2007 ; Bengtson and Roth , 2008 ) . The OntoNotes-5 .0 dataset , which is released for the CoNLL-2012 Shared Task ( Pradhan et al. , 2012 ) , contains 3,145 annotated documents . These documents come from a wide range of sources which include newswire , bible , transcripts , magazines , and web blogs .
positional features that have been employed by highwe can see , the baseline achieves an F-measure of performing resolvers such as Ng and Cardie ( 2002 ) 57.0 and a resolution accuracy of 48.4 . and Yang et al. ( 2003 ) , as described below . To get a better sense of how strong our baseline Lexical features .
Thus , observing the rationales helps us infer the true 0 . We collect substring rationales for a sentiment classification task ( Pang and Lee , 2004 ) and use them to obtain significant accuracy improvements for each annotator . Our new generative approach exploits the rationales more effectively than our previous `` masking SVM '' approach .
We apply two different priming experiments namely , the cross modal priming and masked priming experiment discussed in ( Forster and Davis , 1984 ; Rastle et al. , 2000 ; Marslen-Wilson et al. , 1994 ; Marslen-Wilson et al. , 2008 ) for Bangla morphologically complex words . Here , the prime is morphologically derived form of the target presented auditorily ( for cross modal priming ) or visually ( for masked priming ) .
Also , they can simply be added and subtracted rather than multiplied and divided in the hundreds of calculations required for a single sentence parse . The expectation parser uses an ATN-like representation for its grammar ( Woods 1970 ) . Its strategy is top-down .
Despite its simplicity , the performance of our approach was on the level with the previously highest reported results on the same test collections . The error rate on sentence boundaries in the Brown corpus was not significantly worse than the lowest quoted before ( Riley 1989 : 0.28 % vs. 0.20 % error rate ) . 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 ) .
Poesio and Vieira ( 1998 ) and Bunescu ( 2003 ) include cases where antecedent and anaphor are coreferent but do not share the same head noun ( different-head coreference ) . We follow our previous work ( Hou et al. , 2013b ) and restrict bridging to non-coreferential cases . We also exclude comparative anaphora ( Modjeska et al. , 2003 ) .
Candidates who are higher up in the polls tend to stay on topic while the candidates with less power attempt to shift topics more often . This is in line with our previous findings from ( Prabhakaran et al. , 2014 ) that candidates with higher power attempt to shift topics less often than others when responding to moderators . It is also in line with the findings by Prabhakaran et al. ( 2013a ) that candidates with higher power tend not to interrupt others .
A minimum-cost assignment thus represents an optimum way to classify the speech segments so that each one tends not to be put into the class that the individual-document classifier disprefers , but at the same time , highly associated speech segments tend not to be put in different classes . 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 . In our view , the contribution of our work is the examination of new types of relationships , not the method by which such relationships are incorporated into the classification decision .
This step significantly reduces the computational burden of the algorithm . 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 ) . To retain word type pairs that are at least twice as likely to be mutual translations than not , the threshold can be raised to 2 .
OAK7 is a rule based English analyser that includes many functionalities ( POS tagger , stemmer , chunker , Named Entity ( NE ) tagger , dependency analyser , parser , etc ) . It provides a fine grained NE recognition covering 100 different NE types ( Sekine , 2008 ) . Given the sparseness of most of these fine-grained NE types , we have merged them in coarser groups : event , facility , location , person , organisation , product , periodx , timex and numex .
However , a major obstacle to this approach is the lack of parallel corpora for model training . Only a few such corpora exist , including the Hansard English-French corpus and the HKUST EnglishChinese corpus ( Wu , 1994 ) . In this paper , we will describe a method which automatically searches for parallel texts on the Web .
Unfortunately , we could not pursue this avenue of research owing to time limitations . In FAQs , Berger and Mittal ( 2000 ) employed a sentence retrieval approach based on a language model where the entire response to an FAQ is considered a sentence , and the questions and answers are embedded in an FAQ document . They complemented this approach with machine learning techniques that automatically learn the weights of different retrieval models .
The translation quality is evaluated by case-insensitive BLEU-4 with the shortest length penalty . The statistical significance test is performed by the re-sampling approach ( Koehn , 2004 ) . To create the baseline system , we use the opensource Joshua 4.0 system ( Ganitkevitch et al. , 2012 ) to build a hierarchical phrase-based ( HPB ) system , and a syntax-augmented MT ( SAMT ) 11 system ( Zollmann and Venugopal , 2006 ) respectively .
Furthermore , our result shows that the graphbased approaches perform quite competitively under the condition of perfect knowledge and perception . Although evaluated on different data sets , this result is consistent with results from previous work ( Gatt and Belz , 2008 ; Gatt et al. , 2009 ) . However , what is more interesting here is that while graph-based approaches perform well when the agent has perfect knowledge of the environment , as its human partner , these approaches literally fall apart with close to 40 % performance degradation when applied to
In our experiment , we annotated a high number of pairs similar in size to the test sets by Finkelstein ( 2002 ) and Gurevych ( 2006 ) . We used the revised experimental setup ( Gurevych , 2005 ) , based on discrete relatedness scores and presentation of word pairs in isolation , that is scalable to the higher number of pairs . We annotated semantic relatedness instead of similarity and included also non noun-noun pairs .
Few established parsing systems have substantial lexicons and even those which employ very comprehensive grammars ( eg . Robinson , 1982 ; Bobrow , 1978 ) consult relatively small lexicons , typically generated by hand . 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 .
For expository reasons we represent the ARG n features of the append relation as separate arguments . Typed feature grammars can be used as the basis for implementations of Head-driven Phrase Structure Grammar ( Pollard and Sag , 1994 ) .3 ( Meurers and Minnen , 1997 ) propose a compilation of lexical rules into TIT definite clauses 2This view of typed feature structures differs from the perspective on typed feature structures as modeling partial information as in ( Carpenter , 1992 ) .
online accessibility of politically oriented texts in particular , however , is a phenomenon that some have gone so far as to say will have a potentially society-changing effect . In the United States , for example , governmental bodies are providing and soliciting political documents via the Internet , with lofty goals in mind : electronic rulemaking ( eRulemaking ) initiatives involving the `` electronic collection , distribution , synthesis , and analysis of public commentary in the regulatory rulemaking process '' , may `` [ alter ] the citizen-government relationship '' ( Shulman and Schlosberg , 2002 ) . Additionally , much media attention has been focused recently on the potential impact that Internet sites may have on politics2 , or at least on political journalism3 .
It would be interesting to evaluate the retrieval effectiveness ( in terms of precision and recall ) of different versions of the synonym class indexing approach in those cases where retrieval using word or subword indexes fails due to a complete mismatch between query and documents . This will become even more interesting when mappings of our synonym identifiers to a large medical thesaurus ( MeSH , ( NLM , 2001 ) ) are incorporated into our system . Alternatively , we may think of user-centered comparative studies ( Hersh et al. , 1995 ) .
Named-entity recognition systems usually use sets of complex hand-crafted rules that employ a gazetteer and a local context ( Krupa and Hausman 1998 ) . In some systems such dependencies are learned from labeled examples ( Bikel et al. 1997 ) . The advantage of the namedentity approach is that the system not only identifies proper names but also determines their semantic class .