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Frontiers of Information Technology & Electronic Engineering >> 2015, Volume 16, Issue 7 doi: 10.1631/FITEE.1400405

BUEES: a bottom-up event extraction system

Research Center for Social Computing and Information Retrieval, Harbin Institute of Technology, Harbin 150001, China

Available online: 2015-07-20

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Abstract

Traditional event extraction systems focus mainly on event type identification and event participant extraction based on pre-specified event type paradigms and manually annotated corpora. However, different domains have different event type paradigms. When transferring to a new domain, we have to build a new event type paradigm and annotate a new corpus from scratch. This kind of conventional event extraction system requires massive human effort, and hence prevents event extraction from being widely applicable. In this paper, we present BUEES, a bottom-up event extraction system, which extracts events from the web in a completely unsupervised way. The system automatically builds an event type paradigm in the input corpus, and then proceeds to extract a large number of instance patterns of these events. Subsequently, the system extracts event arguments according to these patterns. By conducting a series of experiments, we demonstrate the good performance of BUEES and compare it to a state-of-the-art Chinese event extraction system, i.e., a supervised event extraction system. Experimental results show that BUEES performs comparably (5% higher -measure in event type identification and 3% higher -measure in event argument extraction), but without any human effort.

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