Discontinuous Grammar as a Foreign Language

This repository includes the code of the sequence-to-sequence model for discontinuous constituent parsing described in paper Discontinuous Grammar as a Foreign Language. In particular, it uses the in-order+SWAP linearization to deal with discontinuities and yields 95.47 F1 on the English Discontinuous Penn Treebank (DPTB). This implementation is based on the system by Fernandez Astudillo et al. (2020) and reuses part of its code.

Requirements

This implementation was tested on Python 3.6.9, PyTorch 1.1.0 and CUDA 9.0.176. Please run the following command to proceed with the installation:

    cd Disco-Seq2seq-Parser
    pip install -r requirements.txt

For the evaluation, script DISCODOP must be also installed following steps described in https://github.com/andreasvc/disco-dop.

Data

To get shift-reduce linearizations from discontinuous constituent treebanks (for instance, the DPTB), please include train, dev and test splits in discbracket format in the disco_data folder and name them as train.discbracket, dev.discbracket and test.discbracket. Then use the following script:

    ./linearization/generate.sh DPTB

Experiments

To train a model for the DPTB treebank, just execute the following script:

   ./scripts/stack-transformer/con_experiment.sh configs/ptb_roberta.large.sh

To test the trained model on the test split, please run the following command:

    ./scripts/stack-transformer/con_test-test.sh configs/test_roberta_large.sh DATA/dep-parsing/models/DPTB_RoBERTa-large_stnp6x6-seed44/checkpoint_top3-average.pt DATA/dep-parsing/models/DPTB_RoBERTa-large_stnp6x6-seed44/epoch-tests-test/dec-checkpoint-top3-average	

Citation

@misc{fernándezgonzález2021discontinuous,
      title={Discontinuous Grammar as a Foreign Language},
      author={Daniel Fernández-González and Carlos Gómez-Rodríguez},
      year={2021},
      eprint={2110.10431},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
    }

Acknowledgments

We acknowledge the European Research Council (ERC), which has funded this research under the European Union’s Horizon 2020 research and innovation programme (FASTPARSE, grant agreement No 714150), MINECO (ANSWER-ASAP, TIN2017-85160-C2-1-R), MICINN (SCANNER, PID2020-113230RB-C21) Xunta de Galicia (ED431C 2020/11), and Centro de Investigación de Galicia "CITIC", funded by Xunta de Galicia and the European Union (ERDF - Galicia 2014-2020 Program), by grant ED431G 2019/01.