{
 "id": "bigbio/euadr",
 "owner": "bigbio",
 "name": "euadr",
 "downloads": 74,
 "likes": 3,
 "last_modified": "2022-12-22T15:44:36.000Z",
 "stated_licence": "unknown",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [],
 "citation": "@article{VANMULLIGEN2012879,\ntitle = {The EU-ADR corpus: Annotated drugs, diseases, targets, and their relationships},\njournal = {Journal of Biomedical Informatics},\nvolume = {45},\nnumber = {5},\npages = {879-884},\nyear = {2012},\nnote = {Text Mining and Natural Language Processing in Pharmacogenomics},\nissn = {1532-0464},\ndoi = {https://doi.org/10.1016/j.jbi.2012.04.004},\nurl = {https://www.sciencedirect.com/science/article/pii/S1532046412000573},\nauthor = {Erik M. {van Mulligen} and Annie Fourrier-Reglat and David Gurwitz and Mariam Molokhia and Ainhoa Nieto and Gianluca Trifiro and Jan A. Kors and Laura I. Furlong},\nkeywords = {Text mining, Corpus development, Machine learning, Adverse drug reactions},\nabstract = {Corpora with specific entities and relationships annotated are essential to train and evaluate text-mining systems that are developed to extract specific structured information from a large corpus. In this paper we describe an approach where a named-entity recognition system produces a first annotation and annotators revise this annotation using a web-based interface. The agreement figures achieved show that the inter-annotator agreement is much better than the agreement with the system provided annotations. The corpus has been annotated for drugs, disorders, genes and their inter-relationships. For each of the drug–disorder, drug–target, and target–disorder relations three experts have annotated a set of 100 abstracts. These annotated relationships will be used to",
 "signal": "unclear",
 "reason": "The checks could not identify a recognised licence ID in the dataset's metadata.",
 "revision": "da142461b82afb73b7bad03695c61d61a412de4f",
 "stated_evidence": "https://huggingface.co/datasets/bigbio/euadr/blob/da142461b82afb73b7bad03695c61d61a412de4f/README.md",
 "file_evidence": "https://huggingface.co/datasets/bigbio/euadr/tree/da142461b82afb73b7bad03695c61d61a412de4f",
 "card_nc": false
}