This survey paper proposes a clearer view of natural language reasoning in the field of Natural Language Processing (NLP), both conceptually and practically. Conceptually, we provide a distinct definition for natural language reasoning in NLP, based on both philosophy and NLP scenarios, discuss what types of tasks require reasoning, and introduce a taxonomy of reasoning. Practically, we conduct a comprehensive literature review on natural language reasoning in NLP, mainly covering classical logical reasoning, natural language inference, multi-hop question answering, and commonsense reasoning. The paper also identifies and views backward reasoning, a powerful paradigm for multi-step reasoning, and introduces defeasible reasoning as one of the most important future directions in natural language reasoning research. We focus on single-modality unstructured natural language text, excluding neuro-symbolic techniques and mathematical reasoning.
翻译:本综述提出了自然语言处理领域中自然语言推理的更清晰的概念和实践视角。从哲学和NLP场景出发,我们提供了自然语言推理在NLP领域内的明确定义,探讨了哪些类型的任务需要推理,并引入了一个推理分类系统。在实践方面,我们进行了自然语言处理中自然语言推理的全面文献回顾,主要涉及经典的逻辑推理、自然语言推断、多跳问题回答和常识推理。本文还确定了倒向推理作为多步推理的一种强大的范例,并将缺陷推理介绍为自然语言推理研究中最重要的未来方向之一。我们重点关注单模态非结构化自然语言文本,不包括神经符号技术和数学推理。