Transition based dependency parser with state embeddings computed by LSTM RNNs. The difference with the master branch is what is explained in this paper which is activated with the -S option (see below).

• A C++ compiler supporting the C++11 language standard
• Boost libraries
• Eigen (newer versions strongly recommended)
• CMake
• gcc (only tested with gcc version 5.3.0, may be incompatible with earlier versions)

mkdir build
cd build
cmake .. -DEIGEN3_INCLUDE_DIR=/path/to/eigen
make -j2

Having a training.conll file and a development.conll formatted according to the CoNLL data format, to train a parsing model with the LSTM parser type the following at the command line prompt:

java -jar ParserOracleArcStdWithSwap.jar -t -1 -l 1 -c training.conll > trainingOracle.txt
java -jar ParserOracleArcStdWithSwap.jar -t -1 -l 1 -c development.conll > devOracle.txt

parser/lstm-parse -T trainingOracle.txt -d devOracle.txt --hidden_dim 100 --lstm_input_dim 100 --pretrained_dim 100 --rel_dim 20 --action_dim 20 --input_dim 100 -t -P -S

Note-1: these model can be either run with or without pretrained word embeddings, although all the experiments reported in the EMNLP paper are run without.

Note-2: the training process should be stopped when the development result does not substantially improve anymore. Normally, after 5500 iterations.

Note-3: the parser reports (after each iteration) results including punctuation symbols while in the ACL-15 paper we report results excluding them (as it is common practice in those data sets). You can find eval.pl script from the CoNLL-X Shared Task to get the correct numbers.

Having a test.conll file formatted according to the CoNLL data format

java -jar ParserOracleArcStdWithSwap.jar -t -1 -l 1 -c test.conll > testOracle.txt

parser/lstm-parse -T trainingOracle.txt -d testOracle.txt --hidden_dim 100 --lstm_input_dim 100 --pretrained_dim 100 --rel_dim 20 --action_dim 20 --input_dim 100 -P -S -m parser_pos_2_100_100_20_100_12_20-pidXXXXX.params

The model name/id is stored where the parser has been trained. The parser will output the conll file with the parsing result.

TODO

If you make use of this software, please cite the following:

@inproceedings{ballesteros:2015emnlp,
  author={Miguel Ballesteros and Chris Dyer and Noah A. Smith},
  title={Improved Transition-Based Parsing by Modeling Characters instead of Words with LSTMs}
  booktitle={Proc. EMNLP},
  year=2015,
}

This software is released under the terms of the Apache License, Version 2.0.

For questions and usage issues, please contact miguel.ballesteros@upf.edu and cdyer@cs.cmu.edu