In this paper, we present kogito, an open-source tool for generating commonsense inferences about situations described in text. kogito provides an intuitive and extensible interface to interact with natural language generation models that can be used for hypothesizing commonsense knowledge inference from a textual input. In particular, kogito offers several features for targeted, multi-granularity knowledge generation. These include a standardized API for training and evaluating knowledge models, and generating and filtering inferences from them. We also include helper functions for converting natural language texts into a format ingestible by knowledge models - intermediate pipeline stages such as knowledge head extraction from text, heuristic and model-based knowledge head-relation matching, and an ability to define and use custom knowledge relations. We make the code for kogito available at https://github.com/epfl-nlp/kogito along with thorough documentation at https://kogito.readthedocs.io.
翻译:在本文中,我们介绍一个开放源码工具Kogito, 用于对文本中描述的情况产生常识性推断。 kogito提供了一种直观和可扩展的界面,与自然语言生成模型进行互动,这些模型可用于从文本输入中假设常识性知识推断,特别是,kogito为有针对性、多层次的知识生成提供了几个特征,其中包括用于培训和评价知识模型的标准化API,以及生成和过滤这些模型的推断。 我们还包括了将自然语言文本转换成可接受格式的辅助功能,这种格式由知识模型组成——中间管道阶段,例如从文本中提取知识头部,超自然和基于模型的知识头部关系匹配,以及界定和使用习惯知识关系的能力。 我们将在https://github.com/epfl-nlp/kogito上提供 kogito的代码,同时在https://kogito.readthedocs.io上提供详尽的文件。