Implementation of the joint event and entity model described in "Joint Extraction of Events and Entities within a Document Context" by Bishan Yang and Tom M. Mitchell.
If you are using this code in your work, please cite the following publication:
Bishan Yang and Tom Mitchell (2016). Joint Extraction of Events and Entities within a Document Context. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), pp. 289-299
For any questions/issues about the code, please feel free to email Bishan Yang ([email protected]).
@InProceedings{yang2016joint,
author = {Yang, Bishan and Mitchell, Tom},
title = {Joint Extraction of Events and Entities within a Document Context},
booktitle = {Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
year = {2016},
pages = {289--299}
}
cd Release
make clean
make
./Release/JEE
ace.test.conll: test documents in the CoNLL format
ace.test.dependencies.txt: the Stanford dependency parse outputs
ace.test.stanford.ner.txt: the Stanford NER outputs
NER_Type DocID SentID StartOffset,EndOffset
CRF++: Yet Another CRF toolkit (https://taku910.github.io/crfpp/)
AD3 (approximate MAP decoder with Alternating Direction Dual Decomposition) (https://github.com/andre-martins/AD3)
Stanford CoreNLP version 3.6.0 (http://stanfordnlp.github.io/CoreNLP/)
GNU Lesser General Public License v3.0