Event Nugget Detection Task : UMBC systems
نویسندگان
چکیده
This paper described our 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 sentencelevel 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 is quite low; we got F1 measure of 34.14 for UMBC1 and 35.24 for UMBC2.
منابع مشابه
New York University 2016 System for KBP Event Nugget: A Deep Learning Approach
This is the first time New York University (NYU) participates in the event nugget (EN) evaluation of the Text Analysis Conference (TAC). We developed EN systems for both subtasks of event nugget, i.e, EN Task 1: Event Nugget Detection and EN Task 2: Event Nugget Detection and Coreference. The systems are mainly based on our recent research on deep learning for event detection (Nguyen and Grishm...
متن کاملEvent Nugget Detection, Classification and Coreference Resolution using Deep Neural Networks and Gradient Boosted Decision Trees
For the shared task of event nugget detection at TAC 2015 we trained a deep feed forward network achieving an official F1-score of 65.31% for plain annotations, 55.56% for event mention type and 49.16% for the realis value. For the task of Event Coreference Resolution we prototyped a simple baseline using Gradient Boosted Decision Trees achieving an overall average CoNLL score of 70.02%. Our co...
متن کاملHITS at TAC KBP 2015: Entity Discovery and Linking, and Event Nugget Detection
HITS participated in the English Entity Linking and Discovery (EDL) and Event Nugget Detection (EN task 1) tracks at TAC KBP 2015. Our EDL system introduces a novel, interleaved multitasking approach, which allows interaction between interdependent entity linking subtasks while avoiding the structural and algorithmic complexity of joint models. Out of the eight systems that participated in the ...
متن کاملEvent Argument Linking and Event Nugget Detection Task: IHMC DISCERN System Report
We present the design and implementation of three variants of an event-detection system called DISCERN, one that used manually created rules (DISCERN-R), one that used machine-learned rules (DISCERN-ML), and one that combined manual and machine-learned rules (DISCERN-C). All three used linguistic resources (VerbNet, CatVar, Semantic Role Labeling, NER, POS tagging, dependency parsing, and coref...
متن کاملIllinois CCG TAC 2015 Event Nugget, Entity Discovery and Linking, and Slot Filler Validation Systems
This paper describes University of Illinois’s Cognitive Computation Group (UI-CCG)’s submissions for three TAC tracks: Event Nugget Detection/Coreference; Entity Discovery and Linking (EDL); and Slot Filler Validation (SFV). The Event Nugget Detection and Coreference system employs a supervised model for event nugget detection with rich lexical and semantic features while we experiment with bot...
متن کامل