In general, Natural Language Processing (NLP) algorithms exhibit black-box behavior. Users input text and output are provided with no explanation of how the results are obtained. In order to increase understanding and trust, users value transparent processing which may explain derived results and enable understanding of the underlying routines. Many approaches take an opaque approach by default when designing NLP tools and do not incorporate a means to steer and manipulate the intermediate NLP steps. We present an interactive, customizable, visual framework that enables users to observe and participate in the NLP pipeline processes, explicitly manipulate the parameters of each step, and explore the result visually based on user preferences. The visible NLP (VNLP) pipeline design is then applied to a text similarity application to demonstrate the utility and advantages of a visible and transparent NLP pipeline in supporting users to understand and justify both the process and results. We also report feedback on our framework from a modern languages expert.

通常，自然语言处理 (NLP) 算法表现出黑盒行为。用户输入的文本和输出不提供如何获得结果的解释。为了增加理解和信任，用户重视透明的处理，它可以解释导出的结果并能够理解底层的程序。许多方法在设计 NLP 工具时默认采用不透明的方法，并且不包含引导和操作中间 NLP 步骤的方法。我们提出了一个交互式的、可定制的、可视化的框架，使用户能够观察和参与 NLP 管道过程，明确地操纵每个步骤的参数，并根据用户的喜好直观地探索结果。然后将可见 NLP (VNLP) 管道设计应用于文本相似性应用程序，以展示可见和透明 NLP 管道在支持用户理解和证明过程和结果方面的效用和优势。我们还报告了现代语言专家对我们框架的反馈。