Joshi, Aravind K
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Publication Using Entity Features to Classify Implicit Discourse Relations(2010-09-01) Joshi, Aravind K; Louis, Annie; Nenkova, Ani; Prasad, RashmiWe report results on predicting the sense of implicit discourse relations between adjacent sentences in text. Our investigation concentrates on the association between discourse relations and properties of the referring expressions that appear in the related sentences. The properties of interest include coreference information, grammatical role, information status and syntactic form of referring expressions. Predicting the sense of implicit discourse relations based on these features is considerably better than a random baseline and several of the most discriminative features conform with linguistic intuitions. However, these features do not perform as well as lexical features traditionally used for sense prediction.Publication Feature Structures Based Tree Adjoining Grammars(1988-10-01) Joshi, Aravind K; Shanker, K. VijayWe have embedded Tree Adjoining Grammars (TAG) in a feature structure based unification system. The resulting system, Feature Structure based Tree Adjoining Grammars (FTAG), captures the principle of factoring dependencies and recursion, fundamental to TAG's. We show that FTAG has an enhanced descriptive capacity compared to TAG formalism. We consider some restricted versions of this system and some possible linguistic stipulations that can be made. We briefly describe a calculus to represent the structures used by this system, extending on the work of Rounds, and Kasper [Rounds et al. 1986, Kasper et al. 1986)involving the logical formulation of feature structures.Publication A Processing Model for Free Word Order Languages(1995-04-01) Rambow, Owen; Joshi, Aravind KLike many verb-final languages, German displays considerable word-order freedom: there is no syntactic constraint on the ordering of the nominal arguments of a verb, as long as the verb remains in final position. This effect is referred to as “scrambling”, and is interpreted in transformational frameworks as leftward movement of the arguments. Furthermore, arguments from an embedded clause may move out of their clause; this effect is referred to as “long-distance scrambling”. While scrambling has recently received considerable attention in the syntactic literature, the status of long-distance scrambling has only rarely been addressed. The reason for this is the problematic status of the data: not only is long-distance scrambling highly dependent on pragmatic context, it also is strongly subject to degradation due to processing constraints. As in the case of center-embedding, it is not immediately clear whether to assume that observed unacceptability of highly complex sentences is due to grammatical restrictions, or whether we should assume that the competence grammar does not place any restrictions on scrambling (and that, therefore, all such sentences are in fact grammatical), and the unacceptability of some (or most) of the grammatically possible word orders is due to processing limitations. In this paper, we will argue for the second view by presenting a processing model for German.Publication Unification-Based Tree Adjoining Grammars(1991-03-01) Vijay-Shanker, K.; Joshi, Aravind KMany current grammar formalisms used in computational linguistics take a unification-based approach that use structures (called feature structures) containing sets of feature-value pairs. In this paper, we describe a unification-based approach to Tree Adjoining Grammars (TAG). The resulting formalism (UTAG) retains the principle of factoring dependencies and recursion that is fundamental to TAGs. We also extend the definition of UTAG to include the lexicalized approach to TAGs (see [Schabes et al., 1988]). We give some linguistic examples using UTAG and informally discuss the descriptive capacity of UTAG, comparing it with other unificationbased formalisms. Finally, based on the linguistic theory underlying TAGs, we propose some stipulations that can be placed on UTAG grammars. In particular, we stipulate that the feature structures associated with the nodes in an elementary tree are bounded ( there is an analogous stipulation in GPSG). Grammars that satisfy these stipulations are equivalent to TAG. Thus, even with these stipulations, UTAGs have more power than CFG-based unification grammars with the same stipulations.Publication Flexible Margin Selection for Reranking with Full Pairwise Samples(2004-03-22) Shen, Libin; Joshi, Aravind KPerceptron like large margin algorithms are introduced for the experiments with various margin selections. Compared to the previous perceptron reranking algorithms, the new algorithms use full pairwise samples and allow us to search for margins in a larger space. Our experimental results on the data set of [1] show that a perceptron like ordinal regression algorithm with uneven margins can achieve Recall/Precision of 89.5/90.0 on section 23 of Penn Treebank. Our result on margin selection can be employed in other large margin machine learning algorithms as well as in other NLP tasks.Publication Processing Crossed and Nested Dependencies: An Automaton Perspective on the Psycholinguistic Results(1988-09-01) Joshi, Aravind KThe clause-final verbal clusters in Dutch and German (and in general, in West Germanic languages) has been extensively studied in different syntactic theories. Standard Dutch prefers crossed dependencies (between verbs and their arguments) while Standard German prefers nested dependencies. Recently Bach, Brown, and Marslen-Wilson (1986) have investigated the consequences of these differences between Dutch and German for the processing complexity of sentences, containing either crossed or nested dependencies. Stated very simply, their results show that Dutch is 'easier' than German, thus showing that the push-down automaton (PDA) cannot be the universal basis for the human parsing mechanism. They provide an explanation for the inadequacy of PDA in terms of the kinds of partial interpretations the dependencies allow the listener to construct. Motivated by their results and their discussion of these results we introduce a principle of partial interpretation (PPI) and present an automaton, embedded push-down automaton (EPDA) which permits processing of crossed and nested dependencies consistent with PPI. We show that there are appropriate complexity measures (motivated by the discussion in Bach, Brown, and Marslen-Wilson (1986) according to which the processing of crossed dependencies is easier than the processing of nested dependencies. This EPDA characterization of the processing of crossed and nested dependencies is significant because EPDAs are known to be exactly equivalent to Tree Adjoining Grammars (TAG), which are also capable of providing a linguistically motivated analysis for the crossed dependencies of Dutch (Kroch and Santorini 1988). This significance is further enhanced by the fact that two other grammatical formalisms, (Head Grammars (Pollard, 1984) and Combinatory Grammars (Steedman, 1987), also capable of providing analysis for crossed dependencies of Dutch, have been recently shown to be equivalent to TAGS in their generative power. We have also briefly discussed some issues concerning the degree to which grammars directly encode the processing by automata, in accordance with PPI.Publication Living Up to Expectations: Computing Expert Responses(2007-01-01) Joshi, Aravind K; Webber, Bonnie L; Weischedel, RalphIn cooperative man-machine interaction, it is necessary but not sufficient for a system to respond truthfully and informatively to a user's question. In particular, if the system has reason to believe that its planned response might mislead the user, then it must block that conclusion by modifying its response. This paper focuses on identifying and avoiding potentially misleading responses by acknowledging types of 'informing behavior' usually expected of an expert. We attempt to give a formal account of several types of assertions that should be included in response to questions concerning the achievement of some goal (in addition to the simple answer), lest the questioner otherwise be misled.Publication Processing Crossed and Nested Dependencies: An Automaton Perspective on the Psycholinguistic Results(1989-09-01) Joshi, Aravind KThe clause-final verbal clusters in Dutch and German (and in general, in West Germanic languages) have been studied extensively in different syntactic theories. Standard Dutch prefers crossed dependencies (between verbs and their arguments) while Standard German prefers nested dependencies. Recently Bach, Brown, and Marslen-Wilson (1986) have investigated the consequences of these differences between Dutch and German for the processing complexity of sentences, containing either crossed or nested dependencies. Stated very simply, their results show that Dutch is 'easier' than German, thus showing that the push-down automaton (PDA) cannot be the universal basis for the human parsing mechanism. They provide an explanation for the inadequacy of PDA in terms of the kinds of partial interpretations the dependencies allow the listener to construct. Motivated by their results and their discussion of these results we introduce a principle of partial interpretation (PPI) and present an automaton, embedded push-down automaton (EPDA), which permits processing of crossed and nested dependencies consistent with PPI. We show that there are appropriate complexity measures (motivated by the discussion in Bach, Brown, and Marslen-Wilson (1986)) according to which the processing of crossed dependencies is easier than the processing of nested dependencies. We also discuss a case of mixed dependencies. This EPDA characterization of the processing of crossed and nested dependencies is significant because EPDAs are known to be exactly equivalent to Tree Adjoining Grammars (TAG), which are also capable of providing a linguistically motivated analysis for the crossed dependencies of Dutch (Kroch and Santorini 1988). This significance is further enhanced by the fact that two other grammatical formalisms, (Head Grammars (Pollard, 1984) and Combinatory Grammars (Steedman, 1987)), also capable of providing analysis for crossed dependencies of Dutch, have been shown recently to be equivalent to TAGS in their generative power. We have also discussed briefly some issues concerning the EPDAs and their associated grammars, and the relationship between these associated grammars and the corresponding 'linguistic' grammars.Publication Relative compositionality of multi-word expressions: a study of verb-noun (V-N) collocations(2005-10-11) Venkatapathy, Sriram; Joshi, Aravind KRecognition of Multi-word Expressions (MWEs) and their relative compositionality are crucial to Natural Language Processing. Various statistical techniques have been proposed to recognize MWEs. In this paper, we integrate all the existing statistical features and investigate a range of classifiers for their suitability for recognizing the non-compositional Verb-Noun (V-N) collocations. In the task of ranking the V-N collocations based on their relative compositionality, we show that the correlation between the ranks computed by the classifier and human ranking is significantly better than the correlation between ranking of individual features and human ranking. We also show that the properties ‘Distributed frequency of object’ (as defined in [27] ) and ‘Nearest Mutual Information’ (as adapted from [18]) contribute greatly to the recognition of the non-compositional MWEs of the V-N type and to the ranking of the V-N collocations based on their relative compositionality.Publication Sense Annotation in the Penn Discourse Treebank(2008-02-10) Miltsakaki, Eleni; Lee, Alan; Joshi, Aravind K; Robaldo, LivioAn important aspect of discourse understanding and generation involves the recognition and processing of discourse relations. These are conveyed by discourse connectives, i.e., lexical items like because and as a result or implicit connectives expressing an inferred discourse relation. The Penn Discourse TreeBank (PDTB) provides annotations of the argument structure, attribution and semantics of discourse connectives. In this paper, we provide the rationale of the tagset, detailed descriptions of the senses with corpus examples, simple semantic definitions of each type of sense tags as well as informal descriptions of the inferences allowed at each level.
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