#A Graph-based dependency parser using Deep Learning DeepParser is a graph-based dependency parser based on deep learning model. This work has been accepted by ACL2015 as oral long paper. The title of the paper is 《An Effecive Neural Network model for Graph-based Dependency Parsing》. The code is a little messy since I was rushing for the paper deadline. But you can use it to get the experiment results in our paper. I'm still refactoring the code and I'll update the project when I'm finished.

##Project structures model: Trained model for English parser and Chinese Parser
data: Sample dependency data and trained word embeddings (via word2vec)
src: Codes for our three models

##Training and Testing For compiling training code, go to src directory and run:
make dep_parser_train

For compiling testing code, go to src directory and run:
make dep_parser_test