waashk/dblp huggingface dataset:
deep read: a reading comprehension system. this paper describes initial work on <b>deep read</b>, an automated reading comprehension system that accepts arbitrary text input (a story) and answers questions about it. we have acquired a corpus of 60 development and 60 test stories of 3<sup>rd</sup> to 6<sup>th</sup> grade material; each story is followed by short-answer questions (an answer key was also provided). we used these to construct and evaluate a baseline system that uses pattern matching (bag-of-words) techniques augmented with additional automated linguistic processing (stemming, name identification, semantic class identification, and pronoun resolution). this simple system retrieves the sentence containing the answer 30--40% of the time.
long distance pronominalisation and global focus. our corpus of descriptive text contains a significant number of long-distance pronominal references (8.4% of the total). in order to account for how these pronouns are intepreted, we re-examine grosz and sidner's theory of the attentional state, and in particular the use of the global focus to supplement centering theory. our corpus evidence concerning these long-distance pronominal references, as well as studies of the use of descriptions, proper names and ambiguous uses of pronouns, lead us to conclude that a discourse focus stack mechanism of the type proposed by sidner is essential to account for the use of these referring expressions. we suggest revising the grosz & sidner framework by allowing for the possibility that an entity in a focus space may have special status.
ontological promiscuity. to facilitate work in discourse interpretation, the logical form of english sentences should be both close to english and syntactically simple. in this paper i propose a logical notation which is first-order and nonintensional, and for which semantic translation can be naively compositional. the key move is to expand what kinds of entities one allows in one's ontology, rather than complicating the logical notation, the logical form of sentences, or the semantic translation process. three classical problems - opaque adverbials, the distinction between de re and de dicto belief reports, and the problem of identity in intensional contexts - are examined for the difficulties they pose for this logical notation, and it is shown that the difficulties can be overcome. the paper closes with a statement about the view of semantics that is presupposed by this approach.
a theory of parallelism and the case of vp ellipsis. we provide a general account of parallelism in discourse, and apply it to the special case of resolving possible readings for instances of vp ellipsis. we show how several problematic examples are accounted for in a natural and straightforward fashion. the generality of the approach makes it directly applicable to a variety of other types of ellipsis and reference.
interpretation as abduction. an approach to abductive inference developed in the tacitus project has resulted in a dramatic simplification of how the problem of interpreting texts is conceptualized. its use in solving the local pragmatics problems of reference, compound nominals, syntactic ambiguity, and metonymy is described and illustrated. it also suggests an elegant and thorough integration of syntax, semantics, and pragmatics.
parsing with generative models of predicate-argument structure. the model used by the ccg parser of hockenmaier and steedman (2002b) would fail to capture the correct bilexical dependencies in a language with freer word order, such as dutch. this paper argues that probabilistic parsers should therefore model the dependencies in the predicate-argument structure, as in the model of clark et al. (2002), and defines a generative model for ccg derivations that captures these dependencies, including bounded and unbounded long-range dependencies.
creating a ccgbank and a wide-coverage ccg lexicon for german. we present an algorithm which creates a german ccgbank by translating the syntax graphs in the german tiger corpus into ccg derivation trees. the resulting corpus contains 46,628 derivations, covering 95% of all complete sentences in tiger. lexicons extracted from this corpus contain correct lexical entries for 94% of all known tokens in unseen text.
generative models for statistical parsing with combinatory categorial grammar. this paper compares a number of generative probability models for a wide-coverage combinatory categorial grammar (ccg) parser. these models are trained and tested on a corpus obtained by translating the penn treebank trees into ccg normal-form derivations. according to an evaluation of unlabeled word-word dependencies, our best model achieves a performance of 89.9%, comparable to the figures given by collins (1999) for a linguistically less expressive grammar. in contrast to gildea (2001), we find a significant improvement from modeling word-word dependencies.
the formal consequences of using variables in ccg categories. combinatory categorial grammars, ccgs, (steedman 1985) have been shown by weir and joshi (1988) to generate the same class of languages as tree-adjoining grammars (tag), head grammars (hg), and linear indexed grammars (lig). in this paper, i will discuss the effect of using variables in lexical category assignments in ccgs. it will be shown that using variables in lexical categories can increase the weak generative capacity of ccgs beyond the class of grammars listed above.
a semantically-derived subset of english for hardware verification. to verify hardware designs by model checking, circuit specifications are commonly expressed in the temporal logic ctl. automatic conversion of english to ctl requires the definition of an appropriately restricted subset of english. we show how the limited semantic expressibility of ctl can be exploited to derive a <i>hierarchy</i> of subsets. our strategy avoids potential difficulties with approaches that take existing computational semantic analyses of english as their starting point---such as the need to ensure that all sentences in the subset possess a ctl translation.
integration of visual inter-word constraints and linguistic knowledge in degraded text recognition. degraded text recognition is a difficult task. given a noisy text image, a word recognizer can be applied to generate several candidates for each word image. high-level knowledge sources can then be used to select a decision from the candidate set for each word image. in this paper, we propose that visual inter-word constraints can be used to facilitate candidate selection. visual inter-word constraints provide a way to link word images inside the text page, and to interpret them systematically.
exploring the potential of intractable parsers. we revisit the idea of history-based parsing, and present a history-based parsing framework that strives to be simple, general, and flexible. we also provide a decoder for this probability model that is linear-space, optimal, and anytime. a parser based on this framework, when evaluated on section 23 of the penn tree-bank, compares favorably with other state-of-the-art approaches, in terms of both accuracy and speed.
an algorithm for generating referential descriptions with flexible interfaces. most algorithms dedicated to the generation of referential descriptions widely suffer from a fundamental problem: they make too strong assumptions about adjacent processing components, resulting in a limited coordination with their perceptive and linguistics data, that is, the provider for object descriptors and the lexical expression by which the chosen descriptors is ultimately realized. motivated by this deficit, we present a new algorithm that (1) allows for a widely unconstrained, incremental, and goal-driven selection of descriptors, (2) integrates linguistic constraints to ensure the expressibility of the chosen descriptors, and (3) provides means to control the appearance of the created referring expression. hence, the main achievement of our approach lies in providing a core algorithm that makes few assumptions about other processing components and improves the flow of control between modules.
transformation-based interpretation of implicit parallel structures: reconstructing the meaning of "vice versa" and similar linguistic operators. successful participation in dialogue as well as understanding written text requires, among others, interpretation of specifications implicitly conveyed through parallel structures. while those whose reconstruction requires insertion of a missing element, such as gapping and ellipsis, have been addressed to a certain extent by computational approaches, there is virtually no work addressing parallel structures headed by vice versa-like operators, whose reconstruction requires transformation. in this paper, we address the meaning reconstruction of such constructs by an informed reasoning process. the applied techniques include building deep semantic representations, application of categories of patterns underlying a formal reconstruction, and using pragmatically-motivated and empirically justified preferences. we present an evaluation of our algorithm conducted on a uniform collection of texts containing the phrases in question.
planning coherent multisentential text. though most text generators are capable of simply stringing together more than one sentence, they cannot determine which order will ensure a coherent paragraph. a paragraph is coherent when the information in successive sentences follows some pattern of inference or of knowledge with which the hearer is familiar. to signal such inferences, speakers usually use relations that link successive sentences in fixed ways. a set of 20 relations that span most of what people usually say in english is proposed in the rhetorical structure theory of mann and thompson. this paper describes the formalization of these relations and their use in a prototype text planner that structures input elements into coherent paragraphs.
two types of planning in language generation. as our understanding of natural language generation has increased, a number of tasks have been separated from realization and put together under the heading "text planning". so far, however, no-one has enumerated the kinds of tasks a text planner should be able to do. this paper describes the principal lesson learned in combining a number of planning tasks in a planner-realizer: planning and realization should be interleaved, in a limited-commitment planning paradigm, to perform two types of planning: prescriptive and restrictive. limited-commitment planning consists of both prescriptive (hierarchical expansion) planning and of restrictive planning (selecting from options with reference to the status of active goals). at present, existing text planners use prescriptive plans exclusively. however, a large class of planner tasks, especially those concerned with the pragmatic (non-literal) content of text such as style and slant, is most easily performed under restrictive planning. the kinds of tasks suited to each planning style are listed, and a program that uses both styles is described.
when conset meets synset: a preliminary survey of an ontological lexical resource based on chinese characters. this paper describes an on-going project concerning with an ontological lexical resource based on the abundant conceptual information grounded on chinese characters. the ultimate goal of this project is set to construct a cognitively sound and computationally effective character-grounded machine-understandable resource. philosophically, chinese ideogram has its ontological status, but its applicability to the nlp task has not been expressed explicitly in terms of language resource. we thus propose the first attempt to locate chinese characters within the context of ontology. having the primary success in applying it to some nlp tasks, we believe that the construction of this knowledge resource will shed new light on theoretical setting as well as the construction of chinese lexical semantic resources.
planning reference choices for argumentative texts. this paper deals with the reference choices involved in the generation of argumentative text. since a natual segmentation of discourse into attentional spaces is needed to carry out this task, this paper first proposes an architecture for natural language generation that combines hierarchical planning and focus-guided navigation, a work in its own right. while hierarchical planning spans out an attentional hierarchy of the discourse produced, local navigation fills details into the primitive discourse spaces. the usefulness of this architecure actually goes beyond the particular domain of application for which it is developed.a piece of argumentative text such as the proof of a mathematical theorem conveys a sequence of derivations. for each step of derivation, the premises derived in the previous context and the inference method (such as the application of a particular theorem or definition) must be made clear. although not restricted to nominal phrases, our reference decisions are similar to those concerning nominal subsequent referring expressions. based on the work of reichmann, this paper presents a discourse theory that handles reference choices by taking into account both textual distance as well as the attentional hierarchy.
chinese-korean word alignment based on linguistic comparison. word alignment problem between parallel corpora is based on the similar characteristics of two aligned words in two languages. we investigate linguistic-knowledge-based word similarity measures while other previous works heavily rely on statistical information, and their limits will be discussed. linguistic knowledge is acquired from linguistic comparison of all layers between two languages, for chinese and korean in this paper.
information extraction from voicemail. in this paper we address the problem of extracting key pieces of information from voicemail messages, such as the identity and phone number of the caller. this task differs from the named entity task in that the information we are interested in is a subset of the named entities in the message, and consequently, the need to pick the correct subset makes the problem more difficult. also, the caller's identity may include information that is not typically associated with a named entity. in this work, we present three information extraction methods, one based on hand-crafted rules, one based on maximum entropy tagging, and one based on probabilistic transducer induction. we evaluate their performance on both manually transcribed messages and on the output of a speech recognition system.
american sign language generation: multimodal nlg with multiple linguistic channels. software to translate english text into american sign language (asl) animation can improve information accessibility for the majority of deaf adults with limited english literacy. asl natural language generation (nlg) is a special form of multimodal nlg that uses multiple linguistic output channels. asl nlg technology has applications for the generation of gesture animation and other communication signals that are not easily encoded as text strings.
a study on automatically extracted keywords in text categorization. this paper presents a study on if and how automatically extracted keywords can be used to improve text categorization. in summary we show that a higher performance --- as measured by micro-averaged f-measure on a standard text categorization collection --- is achieved when the full-text representation is combined with the automatically extracted keywords. the combination is obtained by giving higher weights to words in the full-texts that are also extracted as keywords. we also present results for experiments in which the keywords are the only input to the categorizer, either represented as unigrams or intact. of these two experiments, the unigrams have the best performance, although neither performs as well as headlines only.
raisins, sultanas, and currants: lexical classification and abstraction via context priming. in this paper we discuss the results of experiments which use a context, essentially an ordered set of lexical items, as the seed from which to build a network representing statistically important relationships among lexical items in some corpus. a metric is then applied to the nodes in the network in order to discover those pairs of items related by high indices of similarity. the goal of this research is to instantiate a class of items corresponding to each item in the priming context. we believe that this instantiation process is ultimately a special case of abstraction over the entire network; in this abstraction, similar nodes are collapsed into metanodes which may then function as if they were single lexical items.
acquiring the meaning of discourse markers. this paper applies machine learning techniques to acquiring aspects of the meaning of discourse markers. three subtasks of acquiring the meaning of a discourse marker are considered: learning its polarity, veridicality, and type (i.e. causal, temporal or additive). accuracy of over 90% is achieved for all three tasks, well above the baselines.
modelling the substitutability of discourse connectives. processing discourse connectives is important for tasks such as discourse parsing and generation. for these tasks, it is useful to know which connectives can signal the same coherence relations. this paper presents experiments into modelling the substitutability of discourse connectives. it shows that substitutability effects distributional similarity. a novel variance-based function for comparing probability distributions is found to assist in predicting substitutability.
spontaneous speech understanding for robust multi-modal human-robot communication. this paper presents a speech understanding component for enabling robust situated human-robot communication. the aim is to gain semantic interpretations of utterances that serve as a basis for multi-modal dialog management also in cases where the recognized word-stream is not grammatically correct. for the understanding process, we designed semantic processable units, which are adapted to the domain of situated communication. our framework supports the specific characteristics of spontaneous speech used in combination with gestures in a real world scenario. it also provides information about the dialog acts. finally, we present a processing mechanism using these concept structures to generate the most likely semantic interpretation of the utterances and to evaluate the interpretation with respect to semantic coherence.
evaluating translational correspondence using annotation projection. recently, statistical machine translation models have begun to take advantage of higher level linguistic structures such as syntactic dependencies. underlying these models is an assumption about the directness of translational correspondence between sentences in the two languages; however, the extent to which this assumption is valid and useful is not well understood. in this paper, we present an empirical study that quantifies the degree to which syntactic dependencies are preserved when parses are projected directly from english to chinese. our results show that although the direct correspondence assumption is often too restrictive, a small set of principled, elementary linguistic transformations can boost the quality of the projected chinese parses by 76% relative to the unimproved baseline.
context-dependent smt model using bilingual verb-noun collocation. in this paper, we propose a new context-dependent smt model that is tightly coupled with a language model. it is designed to decrease the translation ambiguities and efficiently search for an optimal hypothesis by reducing the hypothesis search space. it works through reciprocal incorporation between source and target context: a source word is determined by the context of previous and corresponding target words and the next target word is predicted by the pair consisting of the previous target word and its corresponding source word. in order to alleviate the data sparseness in chunk-based translation, we take a stepwise back-off translation strategy. moreover, in order to obtain more semantically plausible translation results, we use bilingual verb-noun collocations; these are automatically extracted by using chunk alignment and a monolingual dependency parser. as a case study, we experimented on the language pair of japanese and korean. as a result, we could not only reduce the search space but also improve the performance.
tense trees as the "fine structure" of discourse. we present a new compositional tense-aspect deindexing mechanism that makes use of tense trees as components of discourse contexts. the mechanism allows reference episodes to be correctly identified even for embedded clauses and for discourse that involves shifts in temporal perspective, and permits deindexed logical forms to be automatically computed with a small number of deindexing rules.
terminological variation, a means of identifying research topics from texts. after extracting terms from a corpus of titles and abstracts in english, syntactic variation relations are identified amongst them in order to detect research topics. three types of syntactic variations were studied: permutation, expansion and substitution. these syntactic variations yield other relations of formal and conceptual nature. basing on a distinction of the variation relations according to the grammatical function affected in a term - head or modifier - term variants are first clustered into connected components which are in turn clustered into classes. these classes relate two or more components through variations involving a change of head word, thus of topic. the graph obtained reveals the global organisation of research topics in the corpus. a clustering method has been built to compute such classes of research topics.
a hierarchical account of referential accessibility. in this paper, we outline a theory of referential accessibility called veins theory (vt). we show how vt addresses the problem of "left satellites", currently a problem for stack-based models, and show that vt can be used to significantly reduce the search space for antecedents. we also show that vt provides a better model for determining domains of referential accessibility, and discuss how vt can be used to address various issues of structural ambiguity.
a common framework for syntactic annotation. it is widely recognized that the proliferation of annotation schemes runs counter to the need to re-use language resources, and that standards for linguistic annotation are becoming increasingly mandatory. to answer this need, we have developed a representation framework comprised of an abstract model for a variety of different annotation types (e.g., morpho-syntactic tagging, syntactic annotation, co-reference annotation, etc.), which can be instantiated in different ways depending on the annotator s approach and goals. in this paper we provide an overview of our representation framework and demonstrate its applicability to syntactic annotation. we show how the framework can contribute to comparative evaluation and merging of parser output and diverse syntactic annotation schemes.
exploiting syntactic patterns as clues in zero-anaphora resolution. we approach the zero-anaphora resolution problem by decomposing it into intra-sentential and inter-sentential zero-anaphora resolution. for the former problem, syntactic patterns of the appearance of zero-pronouns and their antecedents are useful clues. taking japanese as a target language, we empirically demonstrate that incorporating rich syntactic pattern features in a state-of-the-art learning-based anaphora resolution model dramatically improves the accuracy of intra-sentential zero-anaphora, which consequently improves the overall performance of zero-anaphora resolution.