LGPSolver - Solving Logic Grid Puzzles Automatically
LGPSolver - Solving Logic Grid Puzzles Automatically
复制标题
LGPSolver - 自动解决逻辑网格难题
DOI：
10.18653/v1/2020.findings-emnlp.100
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发表时间：
2020
期刊：
影响因子：
56.9
通讯作者：
Selma Tekir
中科院分区：
文献类型：
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作者：
Elgun Jabrayilzade;Selma Tekir
逻辑格题（Logic Grid Puzzle，LGP）是一种应用题，其任务是解决逻辑问题。问题的约束条件以文本线索的形式给出。一旦这些线索转化为形式逻辑，演绎推理过程提供了解决方案。以全自动的方式解决逻辑网格谜题一直是一个挑战，因为精确理解线索是开发相应的形式逻辑表示所必需的。为了应对这一挑战，我们提出了一个解决方案，使用一个基于DistilBERT的分类器分类到逻辑网格谜题的预定义的谓词类型之一的线索。所提出的解决方案的另一个新奇是识别比较结构的线索。通过从现有词典中收集比较形容词，并利用语义框架捕捉比较量词，可以更好地理解比较结构线索的语义，确保转换为正确的逻辑表示。我们的方法以完全自动化的方式解决逻辑网格难题，在给定的难题数据集上具有100%的准确性，并且远远优于最先进的解决方案。
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.
神经模型一致性的逻辑驱动框架
DOI：
10.18653/v1/d19-1405
发表时间：
2019
期刊：
Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP
影响因子：
--
作者：
Li, Tao;Gupta, Vivek;Mehta, Maitrey;Srikumar, Vivek
通讯作者：
Srikumar, Vivek