tailieunhanh - Báo cáo khoa học: "Using Cross-Entity Inference to Improve Event Extraction"

Event extraction is the task of detecting certain specified types of events that are mentioned in the source language data. The state-of-the-art research on the task is transductive inference (. cross-event inference). In this paper, we propose a new method of event extraction by well using cross-entity inference. In contrast to previous inference methods, we regard entitytype consistency as key feature to predict event mentions. We adopt this inference method to improve the traditional sentence-level event extraction system. . | Using Cross-Entity Inference to Improve Event Extraction Yu Hong Jianfeng Zhang Bin Ma Jianmin Yao Guodong Zhou Qiaoming Zhu School of Computer Science and Technology Soochow University Suzhou City China hongy jfzhang bma jyao gdzhou qmzhu @ Abstract Event extraction is the task of detecting certain specified types of events that are mentioned in the source language data. The state-of-the-art research on the task is transductive inference . cross-event inference . In this paper we propose a new method of event extraction by well using cross-entity inference. In contrast to previous inference methods we regard entitytype consistency as key feature to predict event mentions. We adopt this inference method to improve the traditional sentence-level event extraction system. Experiments show that we can get gain in trigger event identification and more than gain for argument role classification in ACE event extraction. 1 Introduction The event extraction task in ACE Automatic Content Extraction evaluation involves three challenging issues distinguishing events of different types finding the participants of an event and determining the roles of the participants. The recent researches on the task show the availability of transductive inference such as that of the following methods cross-document crosssentence and cross-event inferences. Transductive inference is a process to use the known instances to predict the attributes of unknown instances. As an example given a target event the cross-event inference can predict its type by well using the related events co-occurred with it within the same document. From the sentence 1 He left the company. it is hard to tell whether it is a Transport event in ACE which means that he left the place or an End-Position event which means that he retired from the company. But cross-event inference can use a related event Then he went shopping within 1127 the same document to identify it as a Transport event correctly.