Abstract
Residuated lattices form one of the theoretical backbones of the Lambek Calculus as the standard free models. They also appear in grammatical inference as the syntactic concept lattice, an algebraic structure canonically defined for every language L based on the lattice of all distributionally definable subsets of strings. Recent results show that it is possible to build representations, such as context-free grammars, based on these lattices, and that these representations will be efficiently learnable using distributional learning. In this paper we discuss the use of these syntactic concept lattices as models of Lambek grammars, and use the tools of algebraic logic to try to link the proof theoretic ideas of the Lambek calculus with the more algebraic approach taken in grammatical inference. We can then reconceive grammars of various types as equational theories of the syntactic concept lattice of the language. We then extend this naturally from models based on concatenation of strings, to ones based on concatenations of discontinuous strings, which takes us from context-free formalisms to mildly context sensitive formalisms (multiple context-free grammars) and Morrill’s displacement calculus.
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References
Morrill, G.: Categorial grammar: Logical syntax, semantics and processing. Oxford University Press (2011)
Pentus, M.: Models for the Lambek calculus. Annals of Pure and Applied Logic 75(1-2), 179–213 (1995)
Lambek, J.: The mathematics of sentence structure. American Mathematical Monthly 65(3), 154–170 (1958)
Lambek, J.: Categorial and categorical grammars. In: Oehrle, R.T., Bach, E., Wheeler, D. (eds.) Categorial Grammars and Natural Language Structures, vol. 32, pp. 297–317. D. Reidel (1988)
Buszkowski, W.: Compatibility of a categorial grammar with an associated category system. Mathematical Logic Quarterly 28(14-18), 229–238 (1982)
Buszkowski, W., Penn, G.: Categorial grammars determined from linguistic data by unification. Studia Logica 49(4), 431–454 (1990)
Kanazawa, M.: Learnable classes of categorial grammars. PhD thesis, Stanford University (1994)
Angluin, D.: Inference of reversible languages. Journal of the ACM 29(3), 741–765 (1982)
Angluin, D.: Learning regular sets from queries and counterexamples. Information and Computation 75(2), 87–106 (1987)
de la Higuera, C.: Grammatical inference: learning automata and grammars. Cambridge University Press (2010)
Clark, A.: Distributional Learning of Some Context-Free Languages with a Minimally Adequate Teacher. In: Sempere, J.M., GarcÃa, P. (eds.) ICGI 2010. LNCS, vol. 6339, pp. 24–37. Springer, Heidelberg (2010)
Shirakawa, H., Yokomori, T.: Polynomial-time MAT Learning of C-Deterministic Context-free Grammars. Transactions of the Information Processing Society of Japan 34, 380–390 (1993)
Clark, A.: A Learnable Representation for Syntax Using Residuated Lattices. In: de Groote, P., Egg, M., Kallmeyer, L. (eds.) FG 2009. LNCS (LNAI), vol. 5591, pp. 183–198. Springer, Heidelberg (2011)
Clark, A.: Learning Context Free Grammars with the Syntactic Concept Lattice. In: Sempere, J.M., GarcÃa, P. (eds.) ICGI 2010. LNCS, vol. 6339, pp. 38–51. Springer, Heidelberg (2010)
Yoshinaka, R.: Towards Dual Approaches for Learning Context-Free Grammars Based on Syntactic Concept Lattices. In: Mauri, G., Leporati, A. (eds.) DLT 2011. LNCS, vol. 6795, pp. 429–440. Springer, Heidelberg (2011)
Yoshinaka, R.: Integration of the Dual Approaches in the Distributional Learning of Context-Free Grammars. In: Dediu, A.-H., MartÃn-Vide, C. (eds.) LATA 2012. LNCS, vol. 7183, pp. 538–550. Springer, Heidelberg (2012)
Galatos, N., Jipsen, P., Kowalski, T., Ono, H.: Residuated lattices: an algebraic glimpse at substructural logics. Elsevier (2007)
Costa Florêncio, C.: Learning categorial grammars. PhD thesis, Utrecht University (2003)
Okhotin, A.: Conjunctive grammars. Journal of Automata, Languages and Combinatorics 6(4), 519–535 (2001)
Kanazawa, M.: The Lambek calculus enriched with additional connectives. Journal of Logic, Language and Information 1(2), 141–171 (1992)
Angluin, D.: Learning regular sets from queries and counterexamples. Information and Computation 75(2), 87–106 (1987)
Clark, A.: Towards General Algorithms for Grammatical Inference. In: Hutter, M., Stephan, F., Vovk, V., Zeugmann, T. (eds.) ALT 2010. LNCS (LNAI), vol. 6331, pp. 11–30. Springer, Heidelberg (2010)
Clark, A.: Efficient, correct, unsupervised learning of context-sensitive languages. In: Proceedings of the Fourteenth Conference on Computational Natural Language Learning, Uppsala, Sweden, pp. 28–37. Association for Computational Linguistics (July 2010)
Seki, H., Matsumura, T., Fujii, M., Kasami, T.: On multiple context-free grammars. Theoretical Computer Science 88(2), 229 (1991)
Yoshinaka, R.: Efficient learning of multiple context-free languages with multidimensional substitutability from positive data. Theoretical Computer Science 412(19), 1821–1831 (2011)
Yoshinaka, R., Clark, A.: Polynomial time learning of some multiple context-free languages with a minimally adequate teacher. In: Proceedings of the 15th Conference on Formal Grammar, Copenhagen, Denmark (2010)
Post, E.: Recursive unsolvability of a problem of Thue. The Journal of Symbolic Logic 12(1), 1–11 (1947)
Pereira, F.: Review of Type logical grammar: categorial logic of signs by Glyn Morrill. Computational Linguistics 23(4), 629–635 (1997)
Chomsky, N.: Syntactic Structures. Mouton (1957)
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Clark, A. (2012). Logical Grammars, Logical Theories. In: Béchet, D., Dikovsky, A. (eds) Logical Aspects of Computational Linguistics. LACL 2012. Lecture Notes in Computer Science, vol 7351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31262-5_1
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DOI: https://doi.org/10.1007/978-3-642-31262-5_1
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