datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
coqa
Dataset Card for "coqa"
Dataset Summary
CoQA is a large-scale dataset for building Conversational Question Answering systems.
Our dataset contains 127k questions with answers, obtained from 8k conversations about text passages from seven diverse domains. The questions are conversational, and the answers are free-form text with their corresponding evidence highlighted in the passage.
Supported Tasks and Leaderboards
More Information Needed
Languages… See the full description on the dataset page: https://huggingface.co/datasets/stanfordnlp/coqa.coqar-clarifications-audio
CoQAR Clarifications with synthetic context audio
These audio recordings are AI-generated speech, not recordings of human speakers.
OpenAI tts-1 narrated each exact story using voice alloy, speed 1,
and MP3 output. Long stories are synthesized in ordered parts and joined; see the
audio generation manifest for part boundaries and measured audio properties.
No questions, answers, rationales, or stored model prompts were narrated.
The original appended and inserted configurations… See the full description on the dataset page: https://huggingface.co/datasets/rvashurin/coqar-clarifications-audio.CoQCat
Dataset Card for CoQCat
Dataset Summary
CoQCat is a dataset for Conversational Question Answering in Catalan. It is based on CoQA dataset.
CoQCat comprises 89,364 question-answer pairs, sourced from conversations related to 6,000 text passages from six different domains.
The questions and responses are designed to maintain a conversational tone.
The answers are presented in a free-form text format, with evidence highlighted from the passage.
For the development and test… See the full description on the dataset page: https://huggingface.co/datasets/projecte-aina/CoQCat.coqar-clarifications
CoQAR Clarifications
This dataset pairs 1,000 CoQAR development questions with their original stories and stories damaged by sentence deletion. Each of the resulting 2,000 inputs has five sampled model clarifications. Two configurations reuse the same generated additions and differ only in where those additions are placed.
Configuration
Rows in dev
Clarifications per row
Placement
appended
2,000
5
At the end of the input story
inserted
2,000
5
At the deleted passage… See the full description on the dataset page: https://huggingface.co/datasets/rvashurin/coqar-clarifications.Coq-Changelog-QA
Coq Changelog Q&A Dataset
Dataset Description
The Coq Changelog Q&A Dataset is an extension of the original Coq Changelog Dataset, transforming each changelog entry into two Question–Answer pairs via two distinct prompts. One focuses on a straightforward query about the change itself, while the other aims at the rationale or motivation behind it. By applying both prompts to every changelog entry, the dataset approximately doubles in size compared to the source.… See the full description on the dataset page: https://huggingface.co/datasets/phanerozoic/Coq-Changelog-QA.Coq-HoTT-QA
Coq-HoTT Q&A Dataset
Dataset Description
The Coq-HoTT Q&A Dataset is a conversational extension of the Coq-HoTT Dataset, derived directly from the Coq-HoTT GitHub repository (https://github.com/HoTT/Coq-HoTT). This dataset transforms Homotopy Type Theory (HoTT) content into structured Q&A pairs, bridging the gap between formal mathematics and conversational AI.
Each entry in the dataset represents a mathematical statement, such as a definition or theorem, converted into a… See the full description on the dataset page: https://huggingface.co/datasets/phanerozoic/Coq-HoTT-QA.Coq-UniMath-QA
UniMath Q&A Dataset
Dataset Description
The UniMath Q&A Dataset is a conversational extension of the UniMath Dataset, derived from the UniMath formalization of mathematics (https://github.com/UniMath/UniMath). This dataset transforms Univalent Mathematics content into structured Q&A pairs, making formal mathematical content more accessible through natural language interactions.
Each entry represents a mathematical statement from UniMath (definition, theorem, lemma, etc.)… See the full description on the dataset page: https://huggingface.co/datasets/phanerozoic/Coq-UniMath-QA.Coq-MetaCoq-QA
MetaCoq Q&A Dataset
Dataset Description
The MetaCoq Q&A Dataset is a conversational extension of the MetaCoq Dataset, derived from the MetaCoq formalization of Coq's meta-theory (https://github.com/MetaCoq/metacoq). This dataset transforms meta-theoretical content into structured Q&A pairs, making formal meta-programming and verification concepts more accessible through natural language interactions.
Each entry represents a mathematical statement from MetaCoq (definition… See the full description on the dataset page: https://huggingface.co/datasets/phanerozoic/Coq-MetaCoq-QA.coqa_chat
Dataset Card for CoQA_Chat
Dataset Description
A data set for training LLMs for in-context or Document Question-Answering conversations.
Point of Contact: info@alderley.ai
Dataset Summary
This dataset is an amended version of the CoQA dataset, with the question responses amended to be more conversational in nature, with a greater emphasis on returning contextually relervant infomration with the answer.
CoQA is a large-scale dataset for building Conversational… See the full description on the dataset page: https://huggingface.co/datasets/AlderleyAI/coqa_chat.Luotuo-QA-A-CoQA-Chinese
Dataset Card for luotuo-QA-A
Dataset Summary
CoQA(Conversational Question Answering)数据集是一个用于对话式问答任务的大规模数据集，包含超过127,000个问题及其对应的答案。这些文本来自七个不同领域的段落：儿童故事、文学作品、中学和高中英语考试、新闻、维基百科、Reddit和Science。
CoQA数据集经过简单清洗，共有7012个story，我们在此基础上将整个数据集翻译成了中文并进行了增广，其中每个story中包含5个左右的问题，每个问题进行了5次增广。
由于此数据集是我们Luotuo-QA项目的一部分，我们将它叫做luotuo-QA-A,旨在促进对话式问答在中文语境下的研究和应用。
您可以在这里查看Luotuo-QA项目：https://github.com/LC1332/Luotuo-QA… See the full description on the dataset page: https://huggingface.co/datasets/silk-road/Luotuo-QA-A-CoQA-Chinese.