论文标题
自然语言前提选择：寻找数学文本的支持语句
Natural Language Premise Selection: Finding Supporting Statements for Mathematical Text
论文作者
论文摘要
数学文本是使用单词和数学表达式组合编写的。这种组合以及一种特定的构造句子的方式使得对最先进的NLP工具在数学话语之上理解和推理方面具有挑战性。在这项工作中，我们提出了一项新的NLP任务，即自然的前提选择，该任务用于检索支持定义和支持命题，这些命题可用于为特定语句生成非正式的数学证明。我们还提供了一个数据集NL-PS，可用于评估自然前提选择任务的不同方法。使用不同的基准，我们证明了与任务相关的基本解释挑战。
Mathematical text is written using a combination of words and mathematical expressions. This combination, along with a specific way of structuring sentences makes it challenging for state-of-art NLP tools to understand and reason on top of mathematical discourse. In this work, we propose a new NLP task, the natural premise selection, which is used to retrieve supporting definitions and supporting propositions that are useful for generating an informal mathematical proof for a particular statement. We also make available a dataset, NL-PS, which can be used to evaluate different approaches for the natural premise selection task. Using different baselines, we demonstrate the underlying interpretation challenges associated with the task.
