2021 EMNLP EMNLP 2021

Datasets: A Community Library for Natural Language Processing

Abstract

AbstractThe scale, variety, and quantity of publicly-available NLP datasets has grown rapidly as researchers propose new tasks, larger models, and novel benchmarks. Datasets is a community library for contemporary NLP designed to support this ecosystem. Datasets aims to standardize end-user interfaces, versioning, and documentation, while providing a lightweight front-end that behaves similarly for small datasets as for internet-scale corpora. The design of the library incorporates a distributed, community-driven approach to adding datasets and documenting usage. After a year of development, the library now includes more than 650 unique datasets, has more than 250 contributors, and has helped support a variety of novel cross-dataset research projects and shared tasks. The library is available at https://github.com/huggingface/datasets.

👥 Mega-Team — 32 authors
🌉 Interdisciplinary Bridge — Computer Science and Natural Language Processing
📈 Trend Setter — Databases
🧭 Keyword Pioneer — corpus curation
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Natural Language Processing