Papers › WNUT-2020 Task 1 Overview: Extracting Entities and Relations from Wet Lab Protocols
WNUT-2020 Task 1 Overview: Extracting Entities and Relations from Wet Lab Protocols
Jeniya Tabassum, Sydney Lee, Wei Xu, Alan Ritter
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.
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Named Entity Recognition (NER) | WNUT 2020 | Baseline | F1 | 65.73 | #3 of 3 | Archive leaderboard | report |
| Named Entity Recognition (NER) | WNUT 2020 | Baseline | Precision | 70.06 | #3 of 3 | Archive leaderboard | report |
| Named Entity Recognition (NER) | WNUT 2020 | Baseline | Recall | 61.91 | #3 of 3 | Archive leaderboard | report |
| Relation Extraction | WNUT 2020 | Baseline | F1 | 72.5 | #1 of 1 | Archive leaderboard | report |
| Relation Extraction | WNUT 2020 | Baseline | Precision | 80.1 | #1 of 1 | Archive leaderboard | report |
| Relation Extraction | WNUT 2020 | Baseline | Recall | 66.21 | #1 of 1 | Archive leaderboard | report |
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