Conversational Question Answering (CQA) is a challenging task that aims to generate natural answers for conversational flow questions. In this paper, we propose a pluggable approach for extractive methods that introduces a novel prompt-guided copy mechanism to improve the fluency and appropriateness of the extracted answers. Our approach uses prompts to link questions to answers and employs attention to guide the copy mechanism to verify the naturalness of extracted answers, making necessary edits to ensure that the answers are fluent and appropriate. The three prompts, including a question-rationale relationship prompt, a question description prompt, and a conversation history prompt, enhance the copy mechanism's performance. Our experiments demonstrate that this approach effectively promotes the generation of natural answers and achieves good results in the CoQA challenge.

翻译：对话问答（CQA）是一项具有挑战性的任务，旨在为对话流程中的问题生成自然的答案。本文提出了一种可插入的抽取式方法，引入了一种新颖的提示引导复制机制，以提升所抽取答案的流畅性和适当性。该方法利用提示将问题与答案关联，并通过注意力机制引导复制机制验证所抽取答案的自然性，对其进行必要的编辑，确保答案流畅且合适。三种提示（包括问题-理由关系提示、问题描述提示和对话历史提示）增强了复制机制的效能。实验表明，该方法有效促进了自然答案的生成，并在CoQA挑战中取得了良好结果。