• Local predictor with basic features (Local(b)) • Local predictor with basic features + dependency parsing features (Local(b+p)) • Local predictor with basic features + dependency parsing features + linguistic knowledge features (Local(b+p+l)) • Local predictor + all features introduced in Section 2.1 (Local(all)) • Conditional Random Fields (CRFs): We model a conversation as a sequence of sentences and predict tense using CRFs (Lafferty et al., 2001).
it is much more challenging to predict tense in Chinese conversations and there has not been an effective set of rules to predict Chinese tense so far due to the complexity of language-specific phenomena.