Abstract
Event and argument role detection are frequently conceived as separate tasks. In this work we conceive both processes as one taskin a hybrid event detection approach. Its main component is based on automatic keyword extraction (AKE) using the self-attention mechanism of a BERT transformer model. As a bottleneck for AKE is defining the threshold of the attention values, we propose a novel method for automatic self-attention thresholdselection. It is fueled by core event information, or simply the verb and its arguments as the backbone of an event. These are outputted by a knowledge-based syntactic parser. In a secondstep the event core is enriched with other semantically salient words provided by the transformer model. Furthermore, we propose an automatic self-attention layer and head selectionmechanism, by analyzing which self-attention cells in the BERT transformer contribute most to the hybrid event detection and which linguistic tasks they represent. This approach was integrated in a pipeline event extraction approachand outperforms three state of the art multi-task event extraction methods.- Anthology ID:
- 2022.case-1.4
- Volume:
- Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Venue:
- CASE
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 21–31
- Language:
- URL:
- https://aclanthology.org/2022.case-1.4
- DOI:
- Cite (ACL):
- Thierry Desot, Orphee De Clercq, and Veronique Hoste. 2022. A Hybrid Knowledge and Transformer-Based Model for Event Detection with Automatic Self-Attention Threshold, Layer and Head Selection. In Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE), pages 21–31, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- A Hybrid Knowledge and Transformer-Based Model for Event Detection with Automatic Self-Attention Threshold, Layer and Head Selection (Desot et al., CASE 2022)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2022.case-1.4.pdf