ACE_EVENT
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Joint Event Extraction (ACE) via Structured Prediction with Global Features
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This is the software developed for the paper:
Qi Li, Heng Ji and Liang Huang. 2013. Joint Event Extraction via Structured Prediction. ACL 2013
The resources here are only allowed to be used for research-purpose.
Platform: Java 1.6+
1. Directory
src ---- Java source code
bin ---- binary files from Java source code
data ---- necessary data for the program, e.g. gazetteer.
lib ---- third-party libraries
models ---- models that are developed for the experiments
examples --- includes a sample file/filelist
2. Code
acl.ace.acetypes: codes read and write ACE training data
acl.perceptron: implementation of the perceptron-based joint framework
acl.perceptron.core.BeamSearch: implements the beam-search with early update
acl.perceptron.core.Perceptron.java: training procedure for the averaged perceptron
acl.maxent: implementation of the MaxEnt based baseline
acl.util: utilities to create tokenization/parsing etc.
3. Interface
edu.cuny.qc.perceptron.core.Decoder
Decoder for the joint approach, which takes joint model, apf file and sgm file as input,
and outputs event mentions in apf format.
edu.cuny.qc.maxent.Decoder
Decoder for the pipelined baseline, which takes trigger classifier and argument classifier, apf file, and sgm file as input,
outputs event mentions in apf format.
4. Usage (assuming you are in the home folder of this package):
To test Joint approach:
java -Xmx3G -cp bin;lib/* edu.cuny.qc.perceptron.core.Decoder models/model_April_15_4 examples/input examples/filelist examples/output
To test Pipelined approach:
java -Xmx3G -cp bin;lib/* edu.cuny.qc.maxent.Decoder models/model_trigger_April_15_staged models/model_arg_April_15_staged examples/input examples/filelist examples/output
Note: It needs 3G memory allocation.
Note: delimiter for classpath may vary in different OS.
Contact:
Qi Li
liqiearth@gmail.com
The Graduate Center, CUNY
Prof. Heng Ji
hengjicuny@gmail.com
The Graduate Center, Queens College, CUNY