ParaQA：一个单话轮会话中包含释义反应的问答数据集
ParaQA: A Question Answering Dataset with Paraphrase Responses for Single-Turn Conversation
摘要：
本文提出了ParaQA，一个问答（QA）数据集与多个释义的反应，单轮会话的知识图谱（KG）。该数据集是使用半自动化框架创建的，该框架使用反向翻译等技术生成答案的各种释义。现有的用于在KG上的会话式问答（单轮/多轮）的数据集集中于问题释义并且仅提供最多一个答案口头化。然而，ParaQA包含5000个问答对，每个问题最少有两个，最多有八个独特的释义回答。我们用基线模型补充了数据集，并通过常用的指标（如BLEU和METEOR）说明了具有多个释义答案的优势。ParaQA数据集在一个持久的URI上公开提供，以便在研究社区中更广泛地使用和适应。
英文摘要：
This paper presents ParaQA, a question answering (QA) dataset with multiple paraphrased responses for single-turn conversation over knowledge graphs (KG). The dataset was created using a semi-automated framework for generating diverse paraphrasing of the answers using techniques such as back-translation. The existing datasets for conversational question answering over KGs (single-turn/multi-turn) focus on question paraphrasing and provide only up to one answer verbalization. However, ParaQA contains 5000 question-answer pairs with a minimum of two and a maximum of eight unique paraphrased responses for each question. We complement the dataset with baseline models and illustrate the advantage of having multiple paraphrased answers through commonly used metrics such as BLEU and METEOR. The ParaQA dataset is publicly available on a persistent URI for broader usage and adaptation in the research community.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
