LogicPrpBank: A Corpus for Logical Implication and Equivalence

Autor:	Liu, Zhexiong, Zhang, Jing, Lu, Jiaying, Ma, Wenjing, Ho, Joyce C
Rok vydání:	2024
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	Logic reasoning has been critically needed in problem-solving and decision-making. Although Language Models (LMs) have demonstrated capabilities of handling multiple reasoning tasks (e.g., commonsense reasoning), their ability to reason complex mathematical problems, specifically propositional logic, remains largely underexplored. This lack of exploration can be attributed to the limited availability of annotated corpora. Here, we present a well-labeled propositional logic corpus, LogicPrpBank, containing 7093 Propositional Logic Statements (PLSs) across six mathematical subjects, to study a brand-new task of reasoning logical implication and equivalence. We benchmark LogicPrpBank with widely-used LMs to show that our corpus offers a useful resource for this challenging task and there is ample room for model improvement. Comment: In the 5th AI4ED Workshop, held in conjunction with The 38th AAAI Conference on Artificial Intelligence, February 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2402.09609 Zobrazit plný text záznamu View this record from Arxiv