datquocnguyen / Jointre
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End-to-end neural relation extraction using deep biaffine attention (ECIR 2019)
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python
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End-to-end neural relation extraction using deep biaffine attention
This program provides an implementation of a neural network model for joint extraction of named entities and their semantic relations, as described in my paper:
@InProceedings{NguyenV_ECIR2019,
author = {Dat Quoc Nguyen and Karin Verspoor},
title = {{End-to-end neural relation extraction using deep biaffine attention}},
booktitle = {Proceedings of the 41st European Conference on Information Retrieval},
year = {2019}
}
Installation
jointRE requires the following software packages:
-
Python 2.7 -
$ virtualenv -p python2.7 .DyNet $ source .DyNet/bin/activate $ pip install cython numpy $ pip install dynet==2.0.3
Once you installed the prerequisite packages above, you can clone or download (and then unzip) jointRE.
Usage
jNERE and jECRE correspond to two evaluation setup scenarios NER&RC and EC&RC used in my paper, respectively. Checkout run.sh in scripts folder. It should be self-explanatory.
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