HEVS-TUW at SemEval-2023 Task 8: Ensemble of Language Models and Rule-based Classifiers for Claims Identification and PICO Extraction

Anjani Dhrangadhariya, Wojciech Kusa, Henning Müller, Allan Hanbury


Abstract
This paper describes the HEVS-TUW team submission to the SemEval-2023 Task 8: Causal Claims. We participated in two subtasks: (1) causal claims detection and (2) PIO identification. For subtask 1, we experimented with an ensemble of weakly supervised question detection and fine-tuned Transformer-based models. For subtask 2 of PIO frame extraction, we used a combination of deep representation learning and a rule-based approach. Our best model for subtask 1 ranks fourth with an F1-score of 65.77%. It shows moderate benefit from ensembling models pre-trained on independent categories. The results for subtask 2 warrant further investigation for improvement.
Anthology ID:
2023.semeval-1.246
Volume:
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1776–1782
Language:
URL:
https://aclanthology.org/2023.semeval-1.246
DOI:
10.18653/v1/2023.semeval-1.246
Bibkey:
Cite (ACL):
Anjani Dhrangadhariya, Wojciech Kusa, Henning Müller, and Allan Hanbury. 2023. HEVS-TUW at SemEval-2023 Task 8: Ensemble of Language Models and Rule-based Classifiers for Claims Identification and PICO Extraction. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1776–1782, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
HEVS-TUW at SemEval-2023 Task 8: Ensemble of Language Models and Rule-based Classifiers for Claims Identification and PICO Extraction (Dhrangadhariya et al., SemEval 2023)
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PDF:
https://preview.aclanthology.org/nschneid-patch-3/2023.semeval-1.246.pdf