THUNLP
Datasets
All datasets matching “THUNLP”docredMultiple 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.few_relFewRel is a large-scale few-shot relation extraction dataset, which contains more than one hundred relations and tens of thousands of annotated instances cross different domains.EVIL
EVIL Dataset
Dataset Description
Dataset Summary
The EValuation using ILlicit instructions (EVIL) Dataset is a benchmark grounded in the China and US legal contexts, built to examine large language models’ complicit facilitation responses that guide or enable unlawful user intents. It includes realistic illicit scenarios and intents derived from both jurisdictions’ legal frameworks.
Languages
China (zh): 2,842 samples
US (en): 2,905 samples
Total: 5… See the full description on the dataset page: https://huggingface.co/datasets/thunlp/EVIL.