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Using answer set programming for commonsense reasoning in the Winograd schema challenge. (English) Zbl 1434.68591
Summary: The Winograd Schema Challenge (WSC) is a natural language understanding task proposed as an alternative to the Turing test in 2011. In this work we attempt to solve WSC problems by reasoning with additional knowledge. By using an approach built on top of graph-subgraph isomorphism encoded using Answer Set Programming (ASP) we were able to handle 240 out of 291 WSC problems. The ASP encoding allows us to add additional constraints in an elaboration tolerant manner. In the process we present a graph based representation of WSC problems as well as relevant commonsense knowledge.
Reviewer: Reviewer (Berlin)
68T50 Natural language processing
68N17 Logic programming
68T30 Knowledge representation
ASSAT; WordNet
Full Text: DOI
[1] Bailey, D., Harrison, A., Lierler, Y., Lifschitz, V., and Michael, J.2015. The winograd schema challenge and reasoning about correlation. In In Working Notes of the Symposium on Logical Formalizations of Commonsense Reasoning.
[2] Banarescu, L., Bonial, C., Cai, S., Georgescu, M., Griffitt, K., Hermjakob, U., Knight, K., Koehn, P., Palmer, M., and Schneider, N.2013. Abstract meaning representation for sembanking. In Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse. 178-186.
[3] Baral, C.2003. Knowledge representation, reasoning and declarative problem solving. Cambridge university press. · Zbl 1056.68139
[4] Cordella, L. P., Foggia, P., Sansone, C., and Vento, M.2004. A (sub) graph isomorphism algorithm for matching large graphs. IEEE transactions on pattern analysis and machine intelligence 26, 10, 1367-1372.
[5] Emami, A., De La Cruz, N., Trischler, A., Suleman, K., and Cheung, J. C. K.2018. A knowledge hunting framework for common sense reasoning. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 1949-1958.
[6] Gelfond, M. and Lifschitz, V.1988. The stable model semantics for logic programming. In ICLP/SLP. Vol. 88. 1070-1080.
[7] Isaak, N. and Michael, L.2016. Tackling the winograd schema challenge through machine logical inferences. In STAIRS. Vol. 284. 75-86.
[8] Levesque, H. J., Davis, E., and Morgenstern, L.2011. The winograd schema challenge. In AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning. Vol. 46. 47.
[9] Lin, F. and Zhao, Y.2004. Assat: Computing answer sets of a logic program by sat solvers. Artificial Intelligence 157, 1-2, 115-137. · Zbl 1085.68544
[10] Liu, Q., Jiang, H., Evdokimov, A., Ling, Z.-H., Zhu, X., Wei, S., and Hu, Y.2017. Cause-effect knowledge acquisition and neural association model for solving a set of winograd schema problems. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI). 2344-2350.
[11] Miller, G. A.1995. Wordnet: a lexical database for english. Communications of the ACM 38, 11, 39-41.
[12] Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., and Sutskever, I.2019. Language models are unsupervised multitask learners. OpenAI Blog 1, 8.
[13] Richard-Bollans, A., Gomez Alvarez, L., and Cohn, A. G.2018. The role of pragmatics in solving the winograd schema challenge. In Proceedings of the Thirteenth International Symposium on Commonsense Reasoning (Commonsense 2017). CEUR Workshop Proceedings.
[14] Schüller, P.2014. Tackling winograd schemas by formalizing relevance theory in knowledge graphs. In Fourteenth International Conference on the Principles of Knowledge Representation and Reasoning.
[15] Sharma, A., Vo, N., Aditya, S., and Baral, C.2015a. Identifying various kinds of event mentions in k-parser output. In Proceedings of the The 3rd Workshop on EVENTS: Definition, Detection, Coreference, and Representation. 82-88.
[16] Sharma, A., Vo, N. H., Aditya, S., and Baral, C.2015b. Towards addressing the winograd schema challenge-building and using a semantic parser and a knowledge hunting module. In IJCAI. 1319-1325.
[17] Wolff, J. G.2018. Interpreting winograd schemas via the sp theory of intelligence and its realisation in the sp computer model. arXiv preprint arXiv:1810.04554.
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