1 code implementation • NLP-COVID19 (ACL) 2020 • Timo Möller, Anthony Reina, Raghavan Jayakumar, Malte Pietsch
We present COVID-QA, a Question Answering dataset consisting of 2, 019 question/answer pairs annotated by volunteer biomedical experts on scientific articles related to COVID-19.
no code implementations • EMNLP (MRQA) 2021 • Julian Risch, Timo Möller, Julian Gutsch, Malte Pietsch
To this end, we create an English and a German three-way annotated evaluation dataset containing pairs of answers along with human judgment of their semantic similarity, which we release along with an implementation of the SAS metric and the experiments.
no code implementations • EMNLP (MRQA) 2021 • Timo Möller, Julian Risch, Malte Pietsch
A major challenge of research on non-English machine reading for question answering (QA) is the lack of annotated datasets.