Matthew Stone · 2013
Computational semanticists typically devise applied computer systems simply to work as well as possible, but their work enriches the study of linguistic meaning with important tools, resources and methods which I survey here. To get useful results requires systematizing models from semantics in computational terms. Key computational challenges involve the compositional analysis of sentence meaning; the formalization of lexical meaning and related world knowledge; and modeling context and conversation to connect semantics and pragmatics. Underpinning computational semanticists’ successes in all these areas, we find the distinctive roles of representation, problem solving and learning in computation.
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Patrick Blackburn, Johan Bos · THEORIA An International Journal for Theory History and Foundations of Science · 2008
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Raymond Reiter · Artificial Intelligence · 1977
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Charniak, Eugene, Wilks, Yorick 1939- · 1976
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Cecchini, Flavio Massimiliano, Moretti, Giovanni, Passarotti, Marco et al. · The COCOON platform (University of Paris) · 2022
Computational Historical Semantics is a cooperative project involving the universities of Bielefeld, Frankfurt, Regensburg and Tübingen, coordinated at Goethe-University Frankfurt by an interdisciplinary team led by Bernhard Jussen and Alexander Mehler, and funded by the German Federal Ministry for Education and Research. The text database of the project gathers more than 4000 texts spanning from II to XV Century A.D. The section of the database linked to LiLa comprises 5 texts for a total approximately 1 million words.
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Johan van Benthem · Studies in linguistics and philosophy · 1987
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Gábor Recski · 2017
First and foremost I would like to thank my advisor Andrs Kornai for his ongoing support of my studies and research over the past seven years, during which he supervised all work related to
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Blackburn, Patrick, Kohlhase, Michael · HAL (Le Centre pour la Communication Scientifique Directe) · 2001
ICoS-3 Workshop Proceedings, June 18-19, Siena, Italy. Ouvrage (éditeur).
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S. POLLAK, VELARDI, Paola · IRIS Research product catalog (Sapienza University of Rome) · 2010
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Linguistics Burghard Rieger, Burghard B. Rieger · 2007
this paper will be devoted mainly to those present traits in the field which appear to combine promising components likely to become seminal in the future for a wide range of disciplines in the human sciences and beyond
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Miriam Butt · 2014
1) Automate the process of associating semantic representations with natural language expressions. 2) Use logical representations of natural language expressions to automate the process of drawing inferences.
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Christof Monz · 2000
states of mind, etc. Natural language semantics, as a theory of meaning, determines what the meanings of words of the language are and how to semantically combine elements of a language to build up complex meanings. These meanings are most often represented as formulas in a logical language. Computational semantics investigates the computational properties that formal semantic theories need to enjoy to be applicable to real-world problems. Most approaches in formal semantics are evaluated with respect to criteria like expressiveness, explanatory adequacy, and generality, whereas typical criteria for evaluating approaches in computational semantics include coverage, robustness, eciency, and user-friendliness. Coverage measures the amount of phenomena that can described by a semantic theory. Although coverage should be regarded as a criterion f
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Eijck, D.J.N. (Jan) van, Unger, A. C. (Christina) · Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands · 2010
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Stephen Beale, Sergei Nirenburg, Evelyne Viegas · 1998
Research reported in this paper a) extends the familiar notions of constraints and preferences in computational semantic analysis and generation; b) adapts constraint satisfaction techniques to the requirements of natural language processing; and c) combines i) largescale static knowledge sources (grammars, ontologies and lexicons) with ii) processing algorithms and iii) an advanced control architecture, which guarantees optimal results in near linear-time. The integration of the above has facilitated the implementation of a semantics-based machine translation system between Spanish, English and Chinese. This paper analyzes constraints and preferences in computational semantics. Submission Type: Regular Paper Topic Areas: topic area(s): A3,R2 Author of Record: Stephen Beale (sb@crl.nmsu.edu) Under consideration for other conferences (specify)? none Constraints in Computational Semantics Abstract Research reported in this paper a) extends the familiar notions of constraints and pref...
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2008
It was aimed at bringing together researchers from scientific disciplines to discuss approaches and applications of inference in natural language semantics, ranging from theoretical to implementational issues. In particular, ICoS-1 featured three invited presentations, six contributed talks, and six system demonstrations showing how inference tools are used in natural language applications. The variety of the program was also mirrored by the spectrum of contributing authors, which included researchers from Computational Linguistics, Artificial Intelligence, Computer Science, and Logic. This special issue is derived from ICoS-1. In it we bring together nearly all of the papers presented at the workshop, as well as short descriptions of the systems that were demonstrated at ICoS-1. Before giving a brief description of the contributions, we discuss some generalities. 1 What is Computational Semantics? Semantics is defined as the study of meaning expressed by elements of a language or combinations thereof. Natural language utterances are not just noises or scribbles: they are used to convey information, they are linked with kinds of events, with states of mind,
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Sarah Dessì Schmid, Tim Geelhaar, Bianca Henrichsfreise et al. · Open MIND · 2017
Illustrationen, Diagramme
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Patrick Blackburn, Johan Bos, Michael Kohlhase et al. · Studies in linguistics and philosophy · 2001
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Eijck, Jan, Unger, Christina · Data Archiving and Networked Services (DANS) · 2010
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Workshop Proceedings, Johan Bos, Michael Kohlhase (eds · 2000
ICoS originated from rapid recent developments in the field of computational semantics. Traditional inference tools, such as theorem provers and model generators, are reaching new levels of sophistication and are widely and easily available. Moreover, a wide variety of new tools (statistical and probabilistic methods, ideas from the machine learning community) are likely to be increasingly applied in computational semantics. But most importantly of all, computational semantics seems to have reached the stage where the exploration and development of inference is one of its most pressing tasks--and there's a lot of interesting new work which takes inferential issues seriously. ICoS-2 is organised as a two-day event at the International Conference and Research Center for Computer Science `Schloss Dagstuhl', Germany. Featuring three invited presentations, nine contributed talks, and several system demonstrations, the workshop shows how inference tools are used in natural language applications, ranging from theoretical work to practical implementations. We would like to thank the members of the program committee and several additional referees, who produced highly informative reviews, making it possible to set up the broad and strong program for ICoS-2. Furthermore, we thank Chinaski Worldwide and the steering committee of ICoS for organizational help. The final thanks go to our sponsors for their generous support. Saarbr"ucken, July 2000 Johan Bos & Michael Kohlhase iii
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Augusto, Luis M. · PhilPapers (PhilPapers Foundation) · 2025
Semantics is what gives meaning to a logical language. Introductory books in formal logic almost invariably employ Tarskian semantics, a truth semantics that defines an interpretation as a variable assignment over a non-empty domain of discourse together with a signature interpretation. The problem with this semantics is that it generally dictates the undecidability of classical first-order logic due to an infinity of infinite models. In computational logic, decidability is a synonym for computability, and hence Tarskian semantics is not appropriate. In contrast, Herbrand semantics, also a truth semantics, provides us with finite, propositional-logic style, interpretations that guarantee decidability—even if at the price of fixed interpretations for first-order formulae or theories.
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