Advances in natural language processing have resulted in increased capabilities with respect to multiple tasks. One of the possible causes of the observed performance gains is the introduction of increasingly sophisticated text representations. While many of the new word embedding techniques can be shown to capture particular notions of sentiment or associative structures, we explore the ability of two different word embeddings to uncover or capture the notion of logical shape in text. To this end we present a novel framework that we call Topological Word Embeddings which leverages mathematical techniques in dynamical system analysis and data driven shape extraction (i.e. topological data analysis). In this preliminary work we show that using a topological delay embedding we are able to capture and extract a different, shape-based notion of logic aimed at answering the question "Can we find a circle in a circular argument?"

中文翻译：

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论证拓扑：在逻辑中寻找循环（漏洞）

自然语言处理的进步导致在多个任务方面的能力增加。观察到的性能提升的可能原因之一是引入了越来越复杂的文本表示。虽然可以证明许多新的词嵌入技术可以捕捉特定的情感或关联结构概念，但我们探索了两种不同的词嵌入在揭示或捕捉文本中逻辑形状概念的能力。为此，我们提出了一个新的框架，我们称之为拓扑词嵌入，它利用动态系统分析和数据驱动形状提取（即拓扑数据分析）中的数学技术。在这项初步工作中，我们表明使用拓扑延迟嵌入我们能够捕获和提取不同的，