Abstract
In the current Internet era, numerous unstructured text data in new domains often contain high-volume information. Studies on event extraction in new domains can accelerate building of domain knowledge bases, supporting downstream knowledge-based applications. However, the existing event extraction methods have substantial limitations of the domain. Building event extraction systems from scratch in new domains will heavily depend on the quality and scale of event schemas and annotated data, requiring a lot of human efforts and expertise. Moreover, it is common in the datasets that multiple associated event instances often appear in the same context, heavily hindering event extraction and factuality prediction. This paper summarizes the emerging research field of event extraction in new domains and investigates current research status from three directions: Event schema induction, collective event extraction, and event factuality prediction. In addition, this paper discusses the existing difficulties and challengings and indicates the potential research work to be carried out in the future.
Original language | English |
---|---|
Pages (from-to) | 201-212 |
Number of pages | 12 |
Journal | CAAI Transactions on Intelligent Systems |
Volume | 17 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jan 2022 |
Keywords
- Collective extraction
- Event extraction
- Event factuality prediction
- Event schema induction
- Information extraction
- Knowledge base
- Natural language processing
- New domains