List of existing resources useful for natural language processing in the pharmacovigilance domain

source: type of source, e.g., scientific paper, abstract, drug leaflet, patient forum, tweet, etc.

lang = languages: comma-separated list of 2-letter ISO codes

description: short characterization of the corpus

noteworthiness: any specific feature of this dataset

NER: are entities annotated, and for what types of entities

linking: is entity linking provided, and to what ontologies

REL: are relations annotated

IE = information extraction style: between entity instances (one per pair of entity spans),

KB = knowledge-base style: between entities (one per text and pair of [linked] entities),

CL = text classification style: presence of a relation between entity types (one per text and pair of entity types); if only one type of relation is considered, this is a binary text classification task

REL list: if REL is non null, list of annotated relations

format: CONLL, BRAT, etc.

size: number of language units such as documents, sentences, words (please no megabytes)

publication: reference to a publication (peer-reviewed rather than preprint)

URL: URL where the dataset can be downloaded or is described

name	source	lang	description	noteworthiness	NER	linking	REL	REL list	format	size	publication	URL
TLC	patient forum	de	dataset annotated with layman expressions: Fachterm, Laienbegriff, Abkürzung	layman terms, including their associated technical terms; technical term with a rather layman term	no	no	BRAT	4000 documents	https://www.aclweb.org/anthology/2020.lrec-1.759/	http://macss.dfki.de/data/LREC2020/TLC_v01.tar.gz