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Combining logical and distributional methods in type-logical grammars

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EN
Abstrakty
EN
We propose a low-level way of combining distributional and logical ideas into a single formal system. This will be an instantiation of a more general system, adding weights to proof rules. These weights will not measure some sort of “confidence the proof is valid”, but Rather act as a way to prefer some proofs over others, where preference can mean “easier to process (for humans)” or “more coherent (combining words that make sense together)”. The resulting system of weighted theorem proving can be implemented either as a best-first proof serach strategy or as a polynomial-time approximation of proof search for NP-complete parsing problems.
Rocznik
Strony
287--317
Opis fizyczny
Bibliogr. 34 poz., rys.
Twórcy
autor
  • LIRMM, Montpellier University, CNRS
Bibliografia
  • [1] Anne Abeillé, Lionel Clément, and François Toussenel (2003), Building a Treebank for French, in Anne Abeillé, editor, Treebanks, volume 20 of Text, Speech and Language Technology, pp. 165-187, Springer.
  • [2] Lasha Abzianidze (2017), A natural proof system for natural language, Ph.D. thesis, Tilburg University.
  • [3] Nicolas Asher and Alex Lascarides (2003), Logics of Conversation, Cambridge University Press.
  • [4] Emmon Bach, Colin Brown, and William Marslen-Wilson (1986), Crossed and Nested Dependencies in German and Dutch: A Psycholinguistic Study, Language and Cognitive Processes, 1 (4):249-262.
  • [5] Patrick Baillot and Virgile Mogbil (2004), Soft Lambda-calculus: A Language for Polynomial Time Computation, in Foundations of software science and computation structures, pp. 27-41, Springer.
  • [6] Srinivas Bangalore and Aravind Joshi (2011), Supertagging: Using Complex Lexical Descriptions in Natural Language Processing, MIT Press, Cambridge, Massachusetts.
  • [7] Marco Baroni, Silvia Bernardini, Adriano Ferraresi, and Eros Zanchetta (2009), The WaCky Wide Web: A Collection of Very Large Linguistically Processed Web-Crawled Corpora, Language Resources and Evaluation, 43 (3):209-226.
  • [8] Marco Baroni and Alessandro Lenci (2010), Distributional Memory: A General Framework for Corpus-based Semantics, Computational Linguistics, 36 (4):673-721.
  • [9] Adam Berger, Stephen Della Pietra, and Vincent Della Pietra (1996), A Maximum Entropy Approach to Natural Language Processing, Computational Linguistics, 22 (1):39-71.
  • [10] Guillaume Bonfante and Philippe de Groote (2001), Stochastic Lambek Categorial Grammars, in Geert-Jan Kruijff, Larry Moss, and Richard T. Oehrle, editors, Proceedings of FGMOL 2001, volume 53 of Electronic Notes in Theoretical Computer Science, Elsevier.
  • [11] Johan Bos and Katja Markert (2005), Recognising Textual Entailment with Logical Inference, in Proceedings of the 2005 Conference on Empirical Methods in Natural Language Processing (EMNLP 2005), pp. 628-635.
  • [12] Vincent Danos (1990), La logique linéaire appliquée à l’étude de divers processus de normalisation (principalement du λ-calcul) [Linear logic applied to the study of various normalisation processes (mainly of the lambda calculus)], Ph.D. thesis, University of Paris VII.
  • [13] Vincent Danos and Laurent Regnier (1989), The Structure of Multiplicatives, Archive for Mathematical Logic, 28:181-203.
  • [14] Jean-Philippe Fauconnier (2016), Acquisition de liens sémantiques à partir d’éléments de mise en forme des textes : exploitation des structures énumératives [Acquisition of semantic relations from text layout elements: exploitation of enumerative structures], Ph.D. thesis, Université de Toulouse.
  • [15] L. T. F. Gamut (1991), Logic, Language and Meaning, volume 2, The University of Chicago Press.
  • [16] Jean-Yves Girard (1987), Linear Logic, Theoretical Computer Science, 50:1-102.
  • [17] Mark Johnson (1998), Proof Nets and the Complexity of Processing Center-Embedded Constructions, Journal of Logic, Language and Information, 7 (4):443-447.
  • [18] Adam Kilgarriff and Gregory Grefenstette (2003), Introduction to the Special Issue on the Web as Corpus, Computational Linguistics, 29:333-347.
  • [19] Harold W. Kuhn (1955), The Hungarian Method for the Assignment Problem, Naval Research Logistics Quarterly, 2:83-97.
  • [20] Yves Lafont (2004), Soft Linear Logic and Polynomial Time, Theoretical Computer Science, 318 (1):163-180.
  • [21] Joachim Lambek (1958), The Mathematics of Sentence Structure, American Mathematical Monthly, 65:154-170.
  • [22] David M. Magerman (1994), Natural language parsing as statistical pattern recognition, Ph.D. thesis, University of Pennsylvania.
  • [23] Jeff Mitchell and Mirella Lapata (2010), Composition in Distributional Models of Semantics, Cognitive Science, 34:1388-1429.
  • [24] Michael Moortgat (1997), Categorial Type Logics, in Johan van Benthem and Alice ter Meulen, editors, Handbook of Logic and Language, chapter 2, pp. 93-177, Elsevier/MIT Press.
  • [25] Richard Moot (2010), Automated Extraction of Type-logical Supertags from the Spoken Dutch Corpus, in Srinivas Bangalore and Aravind Joshi, editors, Complexity of Lexical Descriptions and its Relevance to Natural Language Processing: A Supertagging Approach, chapter 12, pp. 291-312, MIT Press, Cambridge, Massachusetts.
  • [26] Richard Moot (2014a), Extended Lambek Calculi and First-order Linear Logic, in Claudia Casadio, Bob Coecke, Michael Moortgat, and Philip Scott, editors, Categories and Types in Logic, Language, and Physics: Essays dedicated to Jim Lambek on the Occasion of this 90th Birthday, number 8222 in Lecture Notes in Artificial Intelligence, pp. 297-330, Springer, Heidelberg.
  • [27] Richard Moot (2014b), A Type-logical Treebank for French, Journal of Language Modelling, 2 (2).
  • [28] Richard Moot (2017), The Grail Theorem Prover: Type Theory for Syntax and Semantics, in Zhaohui Luo and Stergios Chatzikyriakidis, editors, Modern Perspectives in Type Theoretical Semantics, Springer.
  • [29] Richard Moot and Christian Retoré (2012), The Logic of Categorial Grammars: A Deductive Account of Natural Language Syntax and Semantics, number 6850 in Lecture Notes in Artificial Intelligence, Springer, Heidelberg.
  • [30] Richard Moot and Christian Retoré (2016), Natural Language Semantics and Computability, Technical report, LIRMM.
  • [31] Glyn Morrill (1998), Incremental Processing and Acceptability, Technical Report LSI-98-46-R, Departament de Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya.
  • [32] Glyn Morrill (2011), Categorial Grammar: Logical Syntax, Semantics, and Processing, Oxford University Press, Oxford.
  • [33] The Nghia Pham (2016), Sentential Representations in Distributional Semantics, Ph.D. thesis, University of Trento.
  • [34] Helmut Schwichtenberg (1982), Complexity of Normalization in the Pure Typed Lambda-Calculus, in The L. E. J. Brouwer Centenary Symposium, pp. 453-457, North-Holland.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
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