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

• DyNet v2.0

  $ 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.