End-to-End Temporal Relation Extraction in the Clinical Domain
Temporal relation extraction is an important task in the clinical domain, as it allows a better understanding of the temporal context of clinical events. In this paper, we present an end-to end temporal relation extraction system for the clinical domain, using the i2b2 2012 Temporal Relation challenge as a benchmark. In our proposal, we fine-tune REBEL —a sequence-to-sequence model for general relation extraction — with temporal annotations and discharge summaries. Our proposal is then able to simultaneously extract relevant clinical entities, time expressions and the temporal relations between them. Our results demonstrate the efectiveness of this approach, achieving reasonable performance on the End-To-End track of the i2b2 2012 Challenge.
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Results from the Paper
| Task | Dataset | Model | Metric Name | Metric Value | Global Rank | Benchmark |
|---|---|---|---|---|---|---|
| Joint Entity and Relation Extraction | 2012 i2b2 Temporal Relations | Finetuned REBEL | Macro F1 | 0.58 | # 1 |
