CPIC at SemEval-2023 Task 7: GPT2-Based Model for Multi-evidence Natural Language Inference for Clinical Trial Data
Mingtong Huang, Junxiang Ren, Lang Liu, Ruilin Song, Wenbo Yin
Abstract
This paper describes our system submitted for SemEval Task 7, Multi-Evidence Natural Language Inference for Clinical Trial Data. The task consists of 2 subtasks. Subtask 1 is to determine the relationships between clinical trial data (CTR) and statements. Subtask 2 is to output a set of supporting facts extracted from the premises with the input of CTR premises and statements. Through experiments, we found that our GPT2-based pre-trained models can obtain good results in Subtask 2. Therefore, we use the GPT2-based pre-trained model to fine-tune Subtask 2. We transform the evidence retrieval task into a binary class task by combining premises and statements as input, and the output is whether the premises and statements match. We obtain a top-5 score in the evaluation phase of Subtask 2.- Anthology ID:
- 2023.semeval-1.53
- 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:
- 397–401
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.53
- DOI:
- 10.18653/v1/2023.semeval-1.53
- Cite (ACL):
- Mingtong Huang, Junxiang Ren, Lang Liu, Ruilin Song, and Wenbo Yin. 2023. CPIC at SemEval-2023 Task 7: GPT2-Based Model for Multi-evidence Natural Language Inference for Clinical Trial Data. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 397–401, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- CPIC at SemEval-2023 Task 7: GPT2-Based Model for Multi-evidence Natural Language Inference for Clinical Trial Data (Huang et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2023.semeval-1.53.pdf