@inproceedings{lv-etal-2019-autohome,
title = "{AUTOHOME}-{ORCA} at {S}em{E}val-2019 Task 8: Application of {BERT} for Fact-Checking in Community Forums",
author = "Lv, Zhengwei and
Liu, Duoxing and
Sun, Haifeng and
Liang, Xiao and
Lei, Tao and
Shi, Zhizhong and
Zhu, Feng and
Yang, Lei",
editor = "May, Jonathan and
Shutova, Ekaterina and
Herbelot, Aurelie and
Zhu, Xiaodan and
Apidianaki, Marianna and
Mohammad, Saif M.",
booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S19-2150/",
doi = "10.18653/v1/S19-2150",
pages = "870--876",
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."
}
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%0 Conference Proceedings
%T AUTOHOME-ORCA at SemEval-2019 Task 8: Application of BERT for Fact-Checking in Community Forums
%A Lv, Zhengwei
%A Liu, Duoxing
%A Sun, Haifeng
%A Liang, Xiao
%A Lei, Tao
%A Shi, Zhizhong
%A Zhu, Feng
%A Yang, Lei
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F lv-etal-2019-autohome
%X 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.
%R 10.18653/v1/S19-2150
%U https://aclanthology.org/S19-2150/
%U https://doi.org/10.18653/v1/S19-2150
%P 870-876
Markdown (Informal)
[AUTOHOME-ORCA at SemEval-2019 Task 8: Application of BERT for Fact-Checking in Community Forums](https://aclanthology.org/S19-2150/) (Lv et al., SemEval 2019)
- AUTOHOME-ORCA at SemEval-2019 Task 8: Application of BERT for Fact-Checking in Community Forums (Lv et al., SemEval 2019)
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.