Chinese tense labelling and causal analysis
Journal
26th International Conference on Computational Linguistics
Pages
2227-2237
ISBN
9784879747020
Date Issued
2016
Author(s)
Abstract
This paper explores the role of tense information in Chinese causal analysis. Both tasks of causal type classification and causal directionality identification are experimented to show the significant improvement gained from tense features. To automatically extract the tense features, a Chinese tense predictor is proposed. Based on large amount of parallel data, our semi-supervised approach improves the dependency-based convolutional neural network (DCNN) models for Chinese tense labelling and thus the causal analysis. ? 1963-2018 ACL.
Type
conference paper