TitleEvent schema induction based on relational co-occurrence over multiple documents
AuthorsJiang, Tingsong
Sha, Lei
Sui, Zhifang
AffiliationKey Laboratory of Computational Linguistics, Ministry of Education, Institute of Computational Linguistics, School of Electronics and Engineering and Computer Science, Peking University, Beijing, China
Issue Date2014
Citation3rd CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2014.Shenzhen, China,496(23-33).
AbstractEvent schema which comprises a set of related events and participants is of great importance with the development of information extraction (IE) and inducing event schema is prerequisite for IE and natural language generation. Event schema and slots are usually designed manually for traditional IE tasks. Methods for inducing event schemas automatically have been proposed recently. One of the fundamental assumptions in event schema induction is that related events tend to appear together to describe a scenario in natural-language discourse, meanwhile previous work only focused on co-occurrence in one document. We find that semantically typed relational tuples co-occurrence over multiple documents is helpful to construct event schema. We exploit the relational tuples co-occurrence over multiple documents by locating the key tuple and counting relational tuples, and build a co-occurrence graph which takes account of co-occurrence information over multiple documents. Experiments show that co-occurrence information over multiple documents can help to combine similar elements of event schema as well as to alleviate incoherence problems. ? Springer-Verlag Berlin Heidelberg 2014.
Appears in Collections:信息科学技术学院

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