A Dataset for Pharmacovigilance in German, French, and Japanese:
  Annotating Adverse Drug Reactions across Languages
Lisa Raithel Hui-Syuan Yeh Shuntaro Yada Cyril Grouin Thomas Lavergne Aurélie Névéol Patrick Paroubek Philippe Thomas Tomohiro Nishiyama Sebastian Möller Eiji Aramaki Yuji Matsumoto Roland Roller Pierre Zweigenbaum
User-generated data sources have gained significance in uncovering Adverse
Drug Reactions (ADRs), with an increasing number of discussions occurring in
the digital world. However, the existing clinical corpora predominantly revolve
around scientific articles in English. This work presents a multilingual corpus
of texts concerning ADRs gathered from diverse sources, including patient fora,
social media, and clinical reports in German, French, and Japanese. Our corpus
contains annotations covering 12 entity types, four attribute types, and 13
relation types. It contributes to the development of real-world multilingual
language models for healthcare. We provide statistics to highlight certain
challenges associated with the corpus and conduct preliminary experiments
resulting in strong baselines for extracting entities and relations between
these entities, both within and across languages.