1. Articles in category: Discourse

    25-48 of 100 « 1 2 3 4 5 »
    1. On the Explicit and Implicit Spatiotemporal Architecture of Narratives of Personal Experience

      Expanding on recent research into the predictability of explicit linguistic spatial information relative to features of discourse structure, we present the results of several machine learning studies which leverage rhetorical relations, events, temporal information, text sequence, and both explicit and implicit linguistic spatial information in three different corpora of narrative discourses. On average, classifiers predict figure, ground, spatial verb and preposition and frame of reference to 75% accuracy, rhetorical relations to 72% accuracy, and events to 76% accuracy (all values have statistical significance above majority class baselines). These results hold independent of the number of authors, subject matter, length and ...
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    2. Event in Compositional Dynamic Semantics. (arXiv:1108.5017v1 [cs.CL])

      We present a framework which constructs an event-style dis- course semantics. The discourse dynamics are encoded in continuation semantics and various rhetorical relations are embedded in the resulting interpretation of the framework. We assume discourse and sentence are distinct semantic objects, that play different roles in meaning evalua- tion. Moreover, two sets of composition functions, for handling different discourse relations, are introduced. The paper first gives the necessary background and motivation for event and dynamic semantics, then the framework with detailed examples will be introduced.
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      Mentions: Loria
    3. Event in Compositional Dynamic Semantics

      We present a framework which constructs an event-style discourse semantics. The discourse dynamics are encoded in continuation semantics and various rhetorical relations are embedded in the resulting interpretation of the framework. We assume discourse and sentence are distinct semantic objects, that play different roles in meaning evaluation. Moreover, two sets of composition functions, for handling different discourse relations, are introduced. The paper first gives the necessary background and motivation for event and dynamic semantics, then the framework with detailed examples will be introduced. Content Type Book ChapterPages 219-234DOI 10.1007/978-3-642-22221-4_15Authors Sai Qian, LORIA & INRIA Nancy Grand-Est, BP 239, 54506 ...
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    4. From Connectives to Argumentative Markers: A Quest for Markers of Argumentative Moves and of Related Aspects of Argumentative Discourse

      Abstract  In this paper, I explore the potential of systematically studying the linguistic surface of discourse for the purposes of identifying markers of argumentative moves and other related categories, such as types of arguments and argumentative strategies. Such a list of argumentative markers can prove useful for the (semi)automatic treatment of a large corpus of texts. After reviewing literature on the linguistic realization of argumentative moves as well as literature on the subject of discourse markers, it becomes clear that the search for representative items of argumentative markers cannot be restricted to those elements marking relations but that it ...
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      Mentions: France Paris
    5. Towards a Discourse-driven Taxonomic Inference Model

      This chapter describes ongoing work, the goal of which is to create a discourse-driven inference model, as well as to construct resources using such a model. The data process consists of texts from two encyclopedias of the medical domain–stylistic properties characteristic of encyclopedia entries constitute the mechanisms underlying the inference model, such as layout-based features alongside with semantic (conceptual) document structuring. Three parts of the model are explained in detail, providing experimental results that are based on language processing techniques: (i) identifying taxonomic document structure by machine learning; (ii) discourse-driven construction of text–hypothesis pairs for examining types of ...
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    6. FootbOWL: Using a Generic Ontology of Football Competition for Planning Match Summaries

      We present a two-layer OWL ontology-based Knowledge Base (KB) that allows for flexible content selection and discourse structuring in Natural Language text Generation (NLG) and discuss its use for these two tasks. The first layer of the ontology contains an application-independent base ontology. It models the domain and was not designed with NLG in mind. The second layer, which is added on top of the base ontology, models entities and events that can be inferred from the base ontology, including inferable logico-semantic relations between individuals. The nodes in the KB are weighted according to learnt models of content selection, such ...
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    7. Identifying discourse connectives in biomedical text.

      Identifying discourse connectives in biomedical text. AMIA Annu Symp Proc. 2010;2010:657-61 Authors: Ramesh BP, Yu H Discourse connectives are words or phrases that connect or relate two coherent sentences or phrases and indicate the presence of discourse relations. Automatic recognition of discourse connectives may benefit many natural language processing applications. In this pilot study, we report the development of the supervised machine-learning classifiers with conditional random fields (CRFs) for automatically identifying discourse connectives in full-text biomedical articles. Our first classifier was trained on the open-domain 1 million token Penn Discourse Tree Bank (PDTB). We performed cross validation on ...
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    8. Comparing Approaches to Tag Discourse Relations

      It is widely accepted that in a text, sentences and clauses cannot be understood in isolation but in relation with each other through discourse relations that may or may not be explicitly marked. Discourse relations have been found useful in many applications such as machine translation, text summarization, and question answering; however, they are often not considered in computational language applications because domain and genre independent robust discourse parsers are very few. In this paper, we analyze existing approaches to identify five discourse relations automatically (namely, comparison, contingency, illustration, attribution, and topic-opinion), and propose a new approach to identify attributive ...
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    9. Semi-supervised Discourse Relation Classification with Structural Learning

      The corpora available for training discourse relation classifiers are annotated using a general set of discourse relations. However, for certain applications, custom discourse relations are required. Creating a new annotated corpus with a new relation taxonomy is a time-consuming and costly process. We address this problem by proposing a semi-supervised approach to discourse relation classification based on Structural Learning. First, we solve a set of auxiliary classification problems using unlabeled data. Second, the learned classifiers are used to extend feature vectors to train a discourse relation classifier. By defining a relevant set of auxiliary classification problems, we show that the ...
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    10. The influence of global discourse on lexical ambiguity resolution

      Abstract  The influence of global discourse on the resolution of lexical ambiguity was examined in a series of naming experiments. Two-sentence passages were constructed to bias either the dominant or the subordinate meaning of a homonym that was embedded in a locally ambiguous sentence. The results provided evidence for the immediate (0-msec interstimulus interval) resolution of lexical ambiguity and were subsequently replicated in Experiment 2, in which an 80-msec stimulus onset asynchrony exposure duration was employed for the homonyms. Strong dominant and subordinate biased discourse contexts activated only the contextually appropriate sense of a homonym. In Experiment 3, each sentence ...
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    11. Categorial Minimalist Grammar. (arXiv:1012.2661v1 [cs.CL])

      We first recall some basic notions on minimalist grammars and on categorial grammars. Next we shortly introduce partially commutative linear logic, and our representation of minimalist grammars within this categorial system, the so-called categorial minimalist grammars. Thereafter we briefly present \lambda\mu-DRT (Discourse Representation Theory) an extension of \lambda-DRT (compositional DRT) in the framework of \lambda\mu calculus: it avoids type raising and derives different readings from a single semantic representation, in a setting which follows discourse structure. We run a complete example which illustrates the various structures and rules that are needed to derive a semantic representation from the ...
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    12. A Discourse and Dialogue Infrastructure for Industrial Dissemination

      We think that modern speech dialogue systems need a prior usability analysis to identify the requirements for industrial applications. In addition, work from the area of the Semantic Web should be integrated. These requirements can then be met by multimodal semantic processing, semantic navigation, interactive semantic mediation, user adaptation/personalisation, interactive service composition, and semantic output representation which we will explain in this paper.We will also describe the discourse and dialogue infrastructure these components develop and provide two examples of disseminated industrial prototypes. Content Type Book ChapterDOI 10.1007/978-3-642-16202-2_12Authors Daniel Sonntag, German Research Center for AI (DFKI), Stuhlsatzenhausweg ...
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    13. Automated annotation

      To automatically annotate an essay, a sentence of the essay is identified and a feature associated with the sentence is determined. In addition, a probability of the sentence being a discourse element is determined by mapping the feature to a model. The model having been generated by a machine learning application based on at least one annotated essay. Furthermore, the essay is annotated based on the probability.
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    14. Why Discourse Structure?

      I come from a strong lineage of discourse folks. Writing a parser for Rhetorical Structure Theory was one of the first class projects I had when I was a grad student. Recently, with the release of the Penn Discourse Treebank, there has been a bit of a flurry of interest in this problem (I had some snarky comments right after ACL about this). I've also talked about why this is a hard problem, but never really about why it is an interesting problem.My thinking about discourse has changed a lot over the years. My current thinking about it ...
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    15. Method and system for determining text coherence

      A method and system for determining text coherence in an essay is disclosed. A method of evaluating the coherence of an essay includes receiving an essay having one or more discourse elements and text segments. The one or more discourse elements are annotated either manually or automatically. A text segment vector is generated for each text segment in a discourse element using sparse random indexing vectors. The method or system then identifies one or more essay dimensions and measures the semantic similarity of each text segment based on the essay dimensions. Finally, a coherence level is assigned to the essay ...
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    16. Learning Recursive Segments for Discourse Parsing. (arXiv:1003.5372v1 [cs.CL])

      Automatically detecting discourse segments is an important preliminary step towards full discourse parsing. Previous research on discourse segmentation have relied on the assumption that elementary discourse units (EDUs) in a document always form a linear sequence (i.e., they can never be nested). Unfortunately, this assumption turns out to be too strong, for some theories of discourse like SDRT allows for nested discourse units. In this paper, we present a simple approach to discourse segmentation that is able to produce nested EDUs. Our approach builds on standard multi-class classification techniques combined with a simple repairing heuristic that enforces global coherence ...
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    17. A Sequential Model for Discourse Segmentation

      Identifying discourse relations in a text is essential for various tasks in Natural Language Processing, such as automatic text summarization, question-answering, and dialogue generation. The first step of this process is segmenting a text into elementary units. In this paper, we present a novel model of discourse segmentation based on sequential data labeling. Namely, we use Conditional Random Fields to train a discourse segmenter on the RST Discourse Treebank, using a set of lexical and syntactic features. Our system is compared to other statistical and rule-based segmenters, including one based on Support Vector Machines. Experimental results indicate that our sequential ...
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    18. Discourse Relations and Document Structure

      This chapter addresses the requirements and linguistic foundations of automatic relational discourse analysis of complex text types such as scientific journal articles. It is argued that besides lexical and grammatical discourse markers, which have traditionally been employed in discourse parsing, cues derived from the logical and generical document structure and the thematic structure of a text must be taken into account. An approach to modelling such types of linguistic information in terms of XML-based multi-layer annotations and to a text-technological representation of additional knowledge sources is presented. By means of quantitative and qualitative corpus analyses, cues and constraints for automatic ...
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      Mentions: Harald Lüngen
    19. Motivations and implications of veins theory: a discussion of discourse cohesion

      Abstract  The paper deals with the cohesion part of a model of global discourse interpretation, usually known as Veins Theory (VT). By taking the notion of nuclearity (though ignoring relations), from the Rhetorical Structure Theory, VT computes strings of discourse units, called veins, from which domains of accessibility can be determined for each discourse unit. VT’s constructs best fit with an incremental view on discourse processing. Linguistic observations that lead to the elaboration of the theory are presented. Cognitive aspects like short-term memory and on-line summarization are explained in terms of VT’s constructs. Complementary remarks are made on ...
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    20. A Study of the Expressive Possibilities of SK-Languages

      In this chapter we will continue the analysis of the expressive possibilities of SK-languages. The collection of examples considered above doesn’t demonstrate the real power of the constructed mathematical model. That is why let’s consider a number of additional examples in order to illustrate some important possibilities of SK-languages concerning the construction of semantic representations of sentences and discourses and describing the pieces of knowledge about the world. The advantages of the theory of SK-languages in comparison, in particular, with Discourse Representation Theory, Episodic Logic, Theory of Conceptual Graphs, and Database Semantics of Natural Language are set forth ...
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    21. A Mathematical Model for Describing Structured Meanings of Natural Language Sentences and Discourses

      The purpose of this chapter is to construct a mathematical model describing a system consisting of ten partial operations on the finite sequences with the elements being structured meanings of Natural Language (NL) expressions. Informally, the goal is to develop a mathematical tool being convenient for building semantic representations both of separate sentences in NL and of complex discourses of arbitrary big length pertaining to technology, medicine, economy, and other fields of professional activity. The starting point for developing this model is the definition of the class of conceptual bases introduced in the previous chapter. The constructed mathematical model includes ...
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    25-48 of 100 « 1 2 3 4 5 »
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