%0 Conference Proceedings %T Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence %A Sun, Chi %A Huang, Luyao %A Qiu, Xipeng %Y Burstein, Jill %Y Doran, Christy %Y Solorio, Thamar %S Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) %D 2019 %8 June %I Association for Computational Linguistics %C Minneapolis, Minnesota %F sun-etal-2019-utilizing %X Aspect-based sentiment analysis (ABSA), which aims to identify fine-grained opinion polarity towards a specific aspect, is a challenging subtask of sentiment analysis (SA). In this paper, we construct an auxiliary sentence from the aspect and convert ABSA to a sentence-pair classification task, such as question answering (QA) and natural language inference (NLI). We fine-tune the pre-trained model from BERT and achieve new state-of-the-art results on SentiHood and SemEval-2014 Task 4 datasets. The source codes are available at https://github.com/HSLCY/ABSA-BERT-pair. %R 10.18653/v1/N19-1035 %U https://aclanthology.org/N19-1035 %U https://doi.org/10.18653/v1/N19-1035 %P 380-385