Event Nugget Detection using Thresholding and Classification Techniques
Citation of Original Publication
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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.