WNUT-2020 Task 1 Overview: Extracting Entities and Relations from Wet Lab Protocols
It introduces a new benchmark for information extraction in the domain of wet lab protocols, which is incremental as it builds on existing NER and RE tasks.
This paper presents the results of the WNUT-2020 task focused on extracting entities and relations from wet lab protocols, involving 13 participants for NER and 2 for RE, with an overview of the task setup, data annotation, and system performances.
This paper presents the results of the wet lab information extraction task at WNUT 2020. This task consisted of two sub tasks: (1) a Named Entity Recognition (NER) task with 13 participants and (2) a Relation Extraction (RE) task with 2 participants. We outline the task, data annotation process, corpus statistics, and provide a high-level overview of the participating systems for each sub task.