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Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence
Chi Sun, Luyao Huang, Xipeng Qiu
arXiv: 1903.09588v1 (cs.CL)
Accepted to NAACL 2019
License: NONEXCLUSIVE-DISTRIB 1.0
Abstract: 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.
Submitted to arXiv on 22 Mar. 2019