AUTOHOME-ORCA at SemEval-2019 Task 8: Application of BERT for Fact-Checking in Community Forums

Zhengwei Lv, Duoxing Liu, Haifeng Sun, Xiao Liang, Tao Lei, Zhizhong Shi, Feng Zhu, Lei Yang

Abstract
Fact checking is an important task for maintaining high quality posts and improving user experience in Community Question Answering forums. Therefore, the SemEval-2019 task 8 is aimed to identify factual question (subtask A) and detect true factual information from corresponding answers (subtask B). In order to address this task, we propose a system based on the BERT model with meta information of questions. For the subtask A, the outputs of fine-tuned BERT classification model are combined with the feature of length of questions to boost the performance. For the subtask B, the predictions of several variants of BERT model encoding the meta information are combined to create an ensemble model. Our system achieved competitive results with an accuracy of 0.82 in the subtask A and 0.83 in the subtask B. The experimental results validate the effectiveness of our system.
Anthology ID:
S19-2150
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
870–876
Language:
URL:
https://aclanthology.org/S19-2150
DOI:
10.18653/v1/S19-2150
Bibkey:
Cite (ACL):
Zhengwei Lv, Duoxing Liu, Haifeng Sun, Xiao Liang, Tao Lei, Zhizhong Shi, Feng Zhu, and Lei Yang. 2019. AUTOHOME-ORCA at SemEval-2019 Task 8: Application of BERT for Fact-Checking in Community Forums. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 870–876, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
AUTOHOME-ORCA at SemEval-2019 Task 8: Application of BERT for Fact-Checking in Community Forums (Lv et al., SemEval 2019)
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PDF:
https://preview.aclanthology.org/paclic-22-ingestion/S19-2150.pdf
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