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            <namePart type="given">Trevor</namePart>
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            <namePart type="given">Yang</namePart>
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    <abstract>Logic grid puzzle (LGP) is a type of word problem where the task is to solve a problem in logic. Constraints for the problem are given in the form of textual clues. Once these clues are transformed into formal logic, a deductive reasoning process provides the solution. Solving logic grid puzzles in a fully automatic manner has been a challenge since a precise understanding of clues is necessary to develop the corresponding formal logic representation. To meet this challenge, we propose a solution that uses a DistilBERT-based classifier to classify a clue into one of the predefined predicate types for logic grid puzzles. Another novelty of the proposed solution is the recognition of comparison structures in clues. By collecting comparative adjectives from existing dictionaries and utilizing a semantic framework to catch comparative quantifiers, the semantics of clues concerning comparison structures are better understood, ensuring conversion to correct logic representation. Our approach solves logic grid puzzles in a fully automated manner with 100% accuracy on the given puzzle datasets and outperforms state-of-the-art solutions by a large margin.</abstract>
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    <identifier type="doi">10.18653/v1/2020.findings-emnlp.100</identifier>
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%0 Conference Proceedings
%T LGPSolver - Solving Logic Grid Puzzles Automatically
%A Jabrayilzade, Elgun
%A Tekir, Selma
%Y Cohn, Trevor
%Y He, Yulan
%Y Liu, Yang
%S Findings of the Association for Computational Linguistics: EMNLP 2020
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F jabrayilzade-tekir-2020-lgpsolver
%X Logic grid puzzle (LGP) is a type of word problem where the task is to solve a problem in logic. Constraints for the problem are given in the form of textual clues. Once these clues are transformed into formal logic, a deductive reasoning process provides the solution. Solving logic grid puzzles in a fully automatic manner has been a challenge since a precise understanding of clues is necessary to develop the corresponding formal logic representation. To meet this challenge, we propose a solution that uses a DistilBERT-based classifier to classify a clue into one of the predefined predicate types for logic grid puzzles. Another novelty of the proposed solution is the recognition of comparison structures in clues. By collecting comparative adjectives from existing dictionaries and utilizing a semantic framework to catch comparative quantifiers, the semantics of clues concerning comparison structures are better understood, ensuring conversion to correct logic representation. Our approach solves logic grid puzzles in a fully automated manner with 100% accuracy on the given puzzle datasets and outperforms state-of-the-art solutions by a large margin.
%R 10.18653/v1/2020.findings-emnlp.100
%U https://aclanthology.org/2020.findings-emnlp.100
%U https://doi.org/10.18653/v1/2020.findings-emnlp.100
%P 1118-1123

Markdown (Informal)

[LGPSolver - Solving Logic Grid Puzzles Automatically](https://aclanthology.org/2020.findings-emnlp.100) (Jabrayilzade & Tekir, Findings 2020)

• LGPSolver - Solving Logic Grid Puzzles Automatically (Jabrayilzade & Tekir, Findings 2020)

ACL

• Elgun Jabrayilzade and Selma Tekir. 2020. LGPSolver - Solving Logic Grid Puzzles Automatically. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 1118–1123, Online. Association for Computational Linguistics.