Does Coreference Resolution Improve Aspect Based Sentiment Analysis?

Abstract

Aspect-Based Sentiment Analysis (ABSA) has generally focused on extracting explicit opinion targets and classifying them into polarities and categories. Most approaches ignore implicitly expressed opinions, even though they make up a significant part of language; in fact, approximately 25% of the targets in the SemEval ABSA 2016 English restaurant reviews (Pontiki et al., 2016) are implicit and are not taken into consideration when training a model. We propose to solve a part of the implicit targets with coreference resolution in order to improve two ABSA tasks: opinion target extraction and aspect category detection. Our results suggest that coreference resolution helps to perform opinion target extraction and aspect category detection, when the latter is handled as a multi-label classification task. The data and code are publicly available on GitHub https://github.com/rosamariaryh/absa-coref