Question answering dataset featured in "Teaching Machines to Read and Comprehend
The main features of deepmind/rc-data are: Data Science Resources, Datasets and Corpora, Question Answering Datasets, Text and Language Datasets.
Open-source alternatives to deepmind/rc-data include: karthikncode/nlp-datasets — This is a list of datasets/corpora for NLP tasks, in reverse chronological order. Suggestions and pull requests are… google-research-datasets/natural-questions — Natural Questions is a large-scale machine learning research dataset designed for training and evaluating open-domain… chinawithfrank/chatbotcourse — This project is a development course and learning curriculum focused on building large language model chatbots. It… brightmart/nlp_chinese_corpus — This is a large-scale collection of curated Chinese text corpora designed for training natural language processing… apachecn/recommendersystems — 介绍推荐系统基本知识，相关算法以及实现。. caesar0301/awesome-public-datasets — A topic-centric list of HQ open datasets.
This is a list of datasets/corpora for NLP tasks, in reverse chronological order. Suggestions and pull requests are welcome. The goal is to make this a collaborative effort to maintain an updated list of quality datasets.
Natural Questions is a large-scale machine learning research dataset designed for training and evaluating open-domain question answering systems. It consists of a corpus of real search queries paired with human-annotated Wikipedia document spans, providing a standardized foundation for advancing automated information retrieval and comprehension technologies. The project distinguishes itself by providing high-quality ground truth data that supports multiple answer formats, including binary, short-form, and long-form responses. By incorporating extractive span annotations and structured documen
This is a large-scale collection of curated Chinese text corpora designed for training natural language processing models. The project provides a variety of datasets, including a deduplicated archive of millions of news articles with titles and keywords, high-quality categorized question-and-answer pairs, and parallel translation corpora. The collection includes millions of aligned Chinese and English sentence pairs used for cross-lingual model training and machine translation development. It also contains filtered question-and-answer data organized by label for the construction of knowledge-
This project is a development course and learning curriculum focused on building large language model chatbots. It provides a structured series of tutorials for creating conversational agents through the application of natural language processing and deep learning models. The materials include a technical walkthrough for implementing neural networks and word embeddings to handle automated question-answering tasks. It also provides a guide for constructing large-scale conversation corpora from external text sources to train and evaluate dialogue systems. The curriculum covers core text analys