Relation Aware Attention Model for Uncertainty Detection in Text
Manjira Sinha, Nilesh Agarwal, Tirthankar Dasgupta · 2020
Uncertainty in text is an important linguistic phenomenon that is relevant in many areas of natural language processing. In this paper, we present a neural approach towards detecting uncertainty cues in texts. We have explored a series of neural network architectures and evaluated the models with respect to three different data sources belonging to domains such as bio-medical texts, privacy policies, and product reviews. Our preliminary analysis showed that the relation aware attention models outperform the existing baseline systems across all the domains. We have also observed for domain specific texts incorporating character level embeddings significantly improves the performance.