Skip to content

thunlp/DocRED

master
Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Code

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
October 29, 2019 14:05
October 17, 2019 17:13
December 1, 2020 11:18

DocRED

Dataset and code for baselines for DocRED: A Large-Scale Document-Level Relation Extraction Dataset

Multiple entities in a document generally exhibit complex inter-sentence relations, and cannot be well handled by existing relation extraction (RE) methods that typically focus on extracting intra-sentence relations for single entity pairs. In order to accelerate the research on document-level RE, we introduce DocRED, a new dataset constructed from Wikipedia and Wikidata with three features:

  • DocRED annotates both named entities and relations, and is the largest human-annotated dataset for document-level RE from plain text.
  • DocRED requires reading multiple sentences in a document to extract entities and infer their relations by synthesizing all information of the document.
  • Along with the human-annotated data, we also offer large-scale distantly supervised data, which enables DocRED to be adopted for both supervised and weakly supervised scenarios.

Codalab

If you are interested in our dataset, you are welcome to join in the Codalab competition at DocRED

Cite

If you use the dataset or the code, please cite this paper:

@inproceedings{yao2019DocRED,
  title={{DocRED}: A Large-Scale Document-Level Relation Extraction Dataset},
  author={Yao, Yuan and Ye, Deming and Li, Peng and Han, Xu and Lin, Yankai and Liu, Zhenghao and Liu, Zhiyuan and Huang, Lixin and Zhou, Jie and Sun, Maosong},
  booktitle={Proceedings of ACL 2019},
  year={2019}
}

About

Dataset and codes for ACL 2019 DocRED: A Large-Scale Document-Level Relation Extraction Dataset.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages