Event Nugget Detection using Thresholding and Classification Techniques
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https://tac.nist.gov/publications/2015/participant.papers/TAC2015.UMBC.proceedings.pdfPermanent Link
http://hdl.handle.net/11603/11584Collections
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Show full item recordDate
2016-11-14Type of Work
5 pagesText
conference paper
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This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.Subjects
Event Nugget DetectionUMBC2
probability
Convolution Neural Network
UMBC Ebiquity Research Group
Abstract
This paper describes the Event Nugget Detection system that we submitted to the TAC KBP 2016 Event Track. We sent out two runs; UMBC1 and UMBC2. UMBC1 is a sentence-level classification system based on Convolution Neural Network and applied the probability to select a word as an event nugget. UMBC2 is the classification model trained from our features using Weka and filtered out low confidence prediction output using threshold. Our performance was low; we got F1 measure of 34.14 for UMBC1 and 35.24 for UMBC2.