Annotate and Identify Modalities, Speech Acts and Finer-Grained Event Types in Chinese Text

Abstract

Discriminating sentences that denote modalities and speech acts from the ones that describe or report events is a fundamental task for accurate event processing. However, little attention has been paid on this issue. No Chinese corpus is available by now with all different types of sentences annotated with their main functionalities in terms of modality, speech act or event. This paper describes a Chinese corpus with all the information annotated. Based on the five event types that are usually adopted in previous studies of event classification, namely state, activity, achievement, accomplishment and semelfactive, we further provide finer-grained categories, considering that each of the finer-grained event types has different semantic entailments. To differentiate them is useful for deep semantic processing and will thus benefit NLP applications such as question answering and machine translation, etc. We also provide experiments to show that the different types of sentences are differentiable with a promising performance.