hrithikpiyush/acl-arc huggingface dataset:
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 . 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 ) .
Previously ( Gerber and Chai 2010 ) , we assessed the importance of various implicit argument feature groups by conducting feature ablation tests . In each test , the discriminative model was retrained and reevaluated without a particular group of features .
jections of the function word and the neighboring phrase are adjacent or separated by an intervening phrase . To model d ( FWi − 1 , S → T ) , d ( FWi +1 , S → T ) , i.e. whether Li , S → T and Ri , S → T extend beyond the neighboring function word phrase pairs , we utilize the pairwise dominance model of Setiawan et al. ( 2009 ) . Taking d ( FWi − 1 , S → T ) as a case in point , this model takes the form Pdom ( d ( FWi − 1 , S → T ) | Yi − 1 , S → T , Yi , S → T ) , where d takes one of the following four dominance values : leftFirst , rightFirst , dontCare , or neither .
A paragraph can be thought of as a grammatical unit in the following sense : it is the discourse unit in which a functional ( or a predicate-argument ) structure can be definitely assigned to sentences/strings . For instance , Sells ( 1985 , p. 8 ) says that the sentence `` Reagan thinks bananas , '' which is otherwise strange , is in fact acceptable if it occurs as an answer to the question `` What is Kissinger 's favorite fruit ? '' The pairing of these two sentences may be said to create a small paragraph .
Semantic Role labeling ( SRL ) was first defined in Gildea and Jurafsky ( 2002 ) . The purpose of SRL task is to identify and classify the semantic roles of each predicate in a sentence .
We used the Asyncronous Javascript And XML ( or AJAX ) paradigm to create the graphical user interface . AJAX function lets the communication works asyncronously between a client and a server through a set of messages based on HTTP protocol and XML ( Garrett , 2005 ) .
While the shift toward knowledge-poor strategies and the use of corpora represented the main trends of anaphora resolution in the 1990s , there are other significant highlights in recent anaphora resolution research . The inclusion of the coreference task in the Sixth and Seventh Message Understanding Conferences ( MUC-6 and MUC-7 ) gave a considerable impetus to the development of coreference resolution algorithms and systems , such as those described in Baldwin et al. ( 1995 ) , Gaizauskas and Humphreys ( 1996 ) , and Kameyama ( 1997 ) . The last decade of the 20th century saw a number of anaphora resolution projects for languages other than English such as French , German , Japanese , Spanish , Portuguese , and Turkish .
The most detailed evaluation of link tokens to date was performed by ( Macklovitch & Hannan , 1996 ) , who trained Brown et al. 's Model 2 on 74 million words of the Canadian Hansards . These authors kindly provided us with the links generated by that model in 51 aligned sentences from a heldout test set .
The outputs of this network are probability estimates computed with a log-linear model ( also known as a maximum entropy model ) , as is done in ( Ratnaparkhi , 1999 ) . Log-linear models have proved successful in a wide variety of applications , and are the inspiration behind one of the best current statistical parsers ( Charniak , 2000 ) . The difference from previous approaches is in the nature of the input to the log-linear model .
For the higherfrequency words , Fisher 's exact test leads to a slightly better recall with the same precision scores ( 0.31 for both tests ) . While we have observed reasonable results with both G2 and Fisher 's exact test , we have not yet discussed how these results compare to the results that can be obtained with a technique commonly used in corpus linguistics based on the mutual information ( MI ) measure ( Church and Hanks 1990 ) : In ( 4 ) , y is the seed term and x a potential target word .
Morphological alterations of a search term have a negative impact on the recall performance of an information retrieval ( IR ) system ( Choueka , 1990 ; J ¨ appinen and Niemist ¨ o , 1988 ; Kraaij and Pohlmann , 1996 ) , since they preclude a direct match between the search term proper and its morphological variants in the documents to be retrieved . In order to cope with such variation , morphological analysis is concerned with the reverse processing of inflection ( e.g. , ` search ed ' , ` search ing ' ) 1 , derivation ( e.g. , ` search er ' or ` search able ' ) and composition ( e.g. , German ` Blut hoch druck ' [ ` high blood pressure ' ] ) .
However as for other types of synonymy , distributional analysis and clustering techniques can be used to develop such resources . For shuffling paraphrases , french alternations are partially described in ( Saint-Dizier , 1999 ) and a resource is available which describes alternation and the mapping verbs/alternations for roughly 1 700 verbs . For complementing this database and for converse constructions , the LADL tables ( Gross , 1975 ) can furthermore be resorted to , which list detailed syntactico-semantic descriptions for 5 000 verbs and 25 000 verbal expressions .
[ [ DO ( he , sweeps ( the floor ) ) ] CAUSE [ BECOME [ clean ( the floor ) ] ] ] Dowty breaks the event described by ( 2 ) into two subevents , the activity of sweeping the floor and its result , the state of the floor being clean . A more recent approach , advocated by Rappaport Hovav and Levin ( 1998 ) , describes a basic set of event templates corresponding to Vendler 's event classes ( Vendler , 1957 ) : ( 3 ) a. [ x ACT <MANNER> ] ( activity ) b. [ x <STATE> ] ( state ) c. [ BECOME [ x <STATE> ] ] ( achievement ) d. [ x CAUSE [ BECOME [ x <STATE> ] ] ] ( accomplishment ) A process called Template Augmentation allows basic event templates to be freely `` augmented '' to any other event template .
Kaji , Kida , and Morimoto ( 1992 ) identify translationally equivalent phrasal segments and replace such equivalents with variables to generate a set of translation patterns . Watanabe ( 1993 ) combines lexical and dependency mappings to form his generalizations . Other similar approaches include those of Cicekli and G ¨ uvenir ( 1996 ) , McTait and Trujillo ( 1999 ) , Carl ( 1999 ) , and Brown ( 2000 ) , inter alia .
`` Semantic grammars '' already exist which describe not only the syntax but also the semantics of natural language . Thus for instance , ( Copestake and Flickinger , 2000 ; Copestake et al. , 2001 ) describes a Head Driven Phrase Structure Grammar ( HPSG ) which supports the parallel construction of a phrase structure ( or derived ) tree and of a semantic representation and ( Dalrymple , 1999 ) show how to equip Lexical Functional grammar ( LFG ) with a glue semantics . These grammars are both efficient and large scale in that they cover an important fragment of the natural language they describe and can be processed by parsers and generators in almost real time .
The reordering models we describe follow our previous work using function word models for translation ( Setiawan et al. , 2007 ; Setiawan et al. , 2009 ) . The core hypothesis in this work is that function words provide robust clues to the reordering patterns of the phrases surrounding them .
The importance of including nonheadwords has become uncontroversial ( e.g. Collins 1999 ; Charniak 2000 ; Goodman 1998 ) . 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 ) . Thus the major innovations of DOP are :
Unlike a document reuse approach , sentence-level approaches need to consider issues of discourse coherence in order to ensure that the extracted combination of sentences is coherent or at least understandable . 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 ) . The appeal of a sentence-level approach is that it supports the generation of a `` combination response '' in situations where there is insufficient evidence for a single document containing a full response , but there is enough evidence for parts of responses .
1Our rules are similar to those from Xu et al. ( 2009 ) . criteria and data used in our experiments are based on the work of Talbot et al. ( 2011 ) . Table 1 shows the results of using the reordering cost as an augmented-loss to the standard treebank objective function .
We present experiments on the two standard coreference resolution datasets , ACE-2004 ( NIST , 2004 ) and OntoNotes-5 .0 ( Hovy et al. , 2006 ) . Our approach results in a substantial reduction in the coreference performance gap between gold and predicted mentions , and significantly outperforms existing stat-of-the-art results on coreference resolution ; in addition , it achieves significant performance improvement on MD for both datasets .
These systems addressed the evaluation issue as follows . • Only qualitative observations of the responses were reported ( no formal evaluation was performed ) ( Lapalme and Kosseim 2003 ; Roy and Subramaniam 2006 ) . • Only an automatic evaluation was performed , which relied on having model responses ( Berger and Mittal 2000 ; Berger et al. 2000 ) .
Goodman then shows by simple induction that subderivations headed by A with external nonterminals at the roots and leaves , internal nonterminals elsewhere have probability 1/a . And subderivations headed by A1 with external nonterminals only at the leaves , internal nonterminals elsewhere , have probability 1/a1 ( Goodman 1996 ) . Goodman 's main theorem is that this construction produces PCFG derivations isomorphic to DOP derivations with equal probability .
• History-based feature models for predicting the next parser action ( Black et al. , 1992 ) . • Support vector machines for mapping histories to parser actions ( Kudo and Matsumoto , 2002 ) . • Graph transformations for recovering nonprojective structures ( Nivre and Nilsson , 2005 ) .
Sima'an ( 1995 ) gave an efficient algorithm for computing the parse tree generated by the most probable derivation , which in some cases is a reasonable approximation of the most probable parse . Goodman ( 1996 , 1998 ) developed a polynomial time PCFG-reduction of DOP1 whose size is linear in the size of the training set , thus converting the exponential number of subtrees to a compact grammar . While Goodman 's method does still not allow for an efficient computation of the most probable parse in DOP1 , it does efficiently compute the `` maximum constituents parse '' , i.e. the parse tree which is most likely to have the largest number of correct constituents .
Adjectives like good allow either verb-subject or verb-object interpretations : a good cook is a cook who cooks well whereas good soup is soup that tastes good or soup that is good to eat . Pustejovsky ( 1995 ) avoids enumerating the various senses for adjectives like fast by exploiting the semantics of the nouns they modify . Pustejovsky treats nouns as having a qualia structure as part of their lexical entries , which among other things , specifies possible events associated with the entity .
Furthermore , we demonstrate that our results carry over successfully to another parser , the Easy-First Parser ( Goldberg and Elhadad 2010 ) ( Section 6 ) . Hohensee and Bender ( 2012 ) have conducted a study on dependency parsing for 21 languages using features that encode whether the values for certain attributes are equal or not for a node and its governor . These features are potentially powerful , because they generalize to the very notion of agreement , away from the specific values of the attributes on which agreement occurs .9 We expect this kind of feature to yield lower gains for Arabic , unless :
The resulting machine must be normalized , either per-state or globally , to obtain a joint or a conditional distribution as desired . Such approaches have been tried recently in restricted cases ( McCallum et al. , 2000 ; Eisner , 2001b ; Lafferty et al. , 2001 ) . Normalization may be postponed and applied instead to the result of combining the FST with other FSTs by composition , union , concatenation , etc. .
f. Two years II have passed since then . The relation between discourse and prosodic phrasing has been examined in some detail by Bing ( 1985 ) , who argues that each noun phrase in an utterance constitutes a separate prosodic phrase unless it is destressed because of reference to previous discourse . Bing also observes that constituents that refer to items newly introduced into a discourse tend to be longer .
as well as a rapid degradation of attachment score with arc length ( from about 93 % for length 1 to 67 % for length 2 ) . By contrast , Turkish ( Oflazer et al. , 2003 ; Atalay et al. , 2003 ) exhibits high root accuracy but consistently low attachment scores ( about 88 % for length 1 and 68 % for length 2 ) . It is noteworthy that Arabic and Turkish , being `` typological outliers '' , show patterns that are different both from each other and from most of the other languages .
A committee-based selection algorithm works with multiple learners , each maintaining a different hypothesis ( perhaps pertaining to different aspects of the problem ) . The candidate examples that lead to the most disagreements among the different learners are considered to have the highest TUV ( Cohn , Atlas , and Ladner 1994 ; Freund et al. 1997 ) . For computationally intensive problems , such as parsing , keeping multiple learners may be impractical .
We run TreeTagger ( Schmid , 1994 ) for tokenization , and used the Giza + + ( Och and Ney , 2003 ) to align the tokenized corpora at the word level . Subsequently , we extracted the bilingual phrase table from the aligned corpora using the Moses toolkit ( Koehn et al. , 2007 ) . Since the resulting phrase table was very large , we eliminated all the entries with identical content in the two languages , and the ones containing phrases longer than 5 words in one of the two sides .
Current advances in research and development of spoken language systems2 can be found , for example , in the proceedings of the DARPA speech and natural language workshops , as well as in publications from participants of the ESPRIT SUNDIAL project . Representative systems are described in Boisen et al. ( 1989 ) , De Mattia and Giachin ( 1989 ) , Niedermair ( 1989 ) , Niemann ( 1990 ) , and Young ( 1989 ) . * Spoken Language Systems Group , Laboratoiy for Computer Science , MIT , Cambridge MA 02139 f This research was supported by DARPA under Contract N00014-89 +1332 , monitored through the Office of Naval Research .
The boundaries that separate phonological phrases are the candidates for prosodic phrase boundaries , since the prosodic phrases of speech consist of one or more phonological phrases . Our rules for phonological word formation are adopted , for the most part , from G & G , Grosjean and Gee ( 1987 ) , and the account of monosyllabic destressing in Selkirk ( 1984 ) . Thus in our analysis , rules of phonological word formation apply to the non-null terminal nodes in a syntax tree .
which is bound to be less certain than the assignment of frames based entirely on existing examples . As a generalization , Briscoe ( 2001 ) notes that lexicons such as COMLEX tend to demonstrate high precision but low recall . Briscoe and Carroll ( 1997 ) report on manually analyzing an open-class vocabulary of 35,000 head words for predicate subcategorization information and comparing the results against the subcategorization details in COMLEX .
In other methods , lexical resources are specifically tailored to meet the requirements of the domain ( Rosario and Hearst , 2001 ) or the system ( Gomez , 1998 ) . Such systems extract information from some types of syntactic units ( clauses in ( Fillmore and Atkins , 1998 ; Gildea and Jurafsky , 2002 ; Hull and Gomez , 1996 ) ; noun phrases in ( Hull and Gomez , 1996 ; Rosario et al. , 2002 ) ) . Lists of semantic relations are designed to capture salient domain information .
Paths between concepts and glosses can be used to calculate similarity/relatedness scores between single words , that contribute to the computation of the overall similarity between the text and the hypothesis . Besides WordNet , the RTE literature documents the use of a variety of lexical information sources ( Bentivogli et al. , 2010 ; Dagan et al. , 2009 ) . These include , just to mention the most popular
Instead it uses a voting mechanism to select the answer given by the majority of methods . The question answering system developed by Chu-Carroll et al. ( 2003 ) belongs to the merging category of approaches , where the output of an individual method can be used as input to a different method ( this corresponds to Burke 's cascade sub-category ) . Because the results of all the methods are comparable , no learning is required : At each stage of the `` cascade of methods , '' the method that performs best is selected .
A good study comparing document categorization algorithms can be found in ( Yang and Liu , 1999 ) . 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 ) . Concerning Arabic , one automatic categorizer has been reported to have been put under operational use to classify Arabic documents ; it is referred to as `` Sakhr 's categorizer '' ( Sakhr , 2004 ) .
where C , is the covariance matrix of x. Using this classification method we can also derive the probability that a case belongs to a particular group ( i.e. , posterior probabilities ) , which is roughly proportional to the Mahalanobis distance from that group centroid . Discriminant analysis has been employed by researchers in automatic text genre detection ( Biber 1993b ; Karlgren and Cutting 1994 ) since it offers a simple and robust solution despite the fact that it presupposes normal distributions of the discriminating variables .
Andrews et al. ( 2009 ) and is based on a generalization of Latent Dirichlet Allocation . This model has previously been shown to provide excellent performance on multiple tasks , including prediction of association norms , word substitution errors , semantic inferences , and word similarity ( Andrews et al. , 2009 ; Silberer and Lapata , 2012 ) . While prior work has used the model only with feature norms and visual attributes , we show that low-level image features are directly compatible with the model and provide improved representations of word meaning .
Then IA would tend to have little use for this property at all since , presumably , every chihuahua would be small and every alsatian large , making each of the combinations -LCB- large , chihuahua -RCB- ( which denotes the empty set ) and -LCB- large , alsatian -RCB- ( the set of all alsatians ) useless . In other words , existing treatments of gradables in GRE fail to take the `` efficiency of language '' into account ( Barwise and Perry 1983 ; see our Section 2 ) . van Deemter GRE with Gradable Properties
Although no longer competitive as end-to-end translation models , the IBM Models , as well as the hidden Markov model ( HMM ) of Vogel , Ney , and Tillmann ( 1996 ) , are still widely used for word alignment . Word alignments are used primarily for extracting minimal translation units for machine translation ( MT ) ( e.g. , phrases [ Koehn , Och , and Marcu 2003 ] and rules [ Galley et al. 2004 ; Chiang et al. 2005 ] ) as well as for MT system combination ( Matusov , Ueffing , and Ney 2006 ) .
Following Miller et al. , 1999 , the IR system ranks documents according to the probability that a document D is relevant given the query Q , P ( D is R IQ ) . Using Bayes Rule , and the fact that P ( Q ) is constant for a given query , and our initial assumption of a uniform a priori
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 . * National Centre for Language Technology , School of Computing , Dublin City University , Glasnevin , Dublin 9 , Ireland .
Gricean maxims belong there ; Section 6 will be devoted to a presentation of the metalevel rules corresponding to them . We have shown elsewhere ( Jensen and Binot 1988 ; Zadrozny 1987a , 1987b ) that natural language programs , such as on-line grammars and dictionaries , can be used as referential levels for commonsense reasoning -- for example , to disambiguate PP attachment . This means that information contained in grammars and dictionaries can be used to constrain possible interpretations of the logical predicates of an object-level theory .
In this representation , features for one predicate will be completely independent from those for every other predicate . Thus rather than a single training procedure , we can actually partition the examples by predicate , and train a 1For a fixed verb , MI is proportional to Keller and Lapata ( 2003 ) 's conditional probability scores for pseudodisambiguation of ( v , n , n ′ ) triples : Pr ( v | n ) = Pr ( v , n ) / Pr ( n ) , which was shown to be a better measure of association than co-occurrence frequency f ( v , n ) . Normalizing by Pr ( v ) ( yielding MI ) allows us to use a constant threshold across all verbs .