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Unified Reverse Dictionary and Definition Modelling

Overview

This repository contains the code and human evaluation outputs for our research on a multi-task model to unify reverse dictionary and definition modelling. The research has been publiched as:

Data

The two papers above used data from different sources. Unfortunately, we do not own any of the data, so please refer to the original papers or links below.

Run

Creates a conda environment named "unified" which has the packages needed to run the code

    conda env create -f environment.yml
    # unified model with shared word embeddings and output layer.
    python code/train_unfied_share.py \
      --batch_size ${BSZ} \
      --save_dir ${SAVE_MODEL_DIR} \
      --summary_logdir ${SAVE_LOG_DIR} \
      --do_train \
      --train_file ${TRAIN_FILE} \
      --dev_file ${DEV_FILE} \
      --embedding_arch ${ARCH} \ # (sgns, char, electra, bert)
      --device ${DEVICE} \
      --do_pred \
      --test_file ${TEST_FILE} \
      --pred_file ${SAVE_PRED_DIR} \
      --pred_direction ${DIRECTION} \ # (embedding, definition)
      --skip

References

@inproceedings{chen-zhao-2022-unified,
    title = "A Unified Model for Reverse Dictionary and Definition Modelling",
    author = "Chen, Pinzhen  and Zhao, Zheng",
    booktitle = "Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
    month = nov,
    year = "2022",
    address = "Online only",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.aacl-short.2",
    pages = "8--13",
}

@inproceedings{chen-zhao-2022-edinburgh,
    title = "{E}dinburgh at {S}em{E}val-2022 Task 1: Jointly Fishing for Word Embeddings and Definitions",
    author = "Chen, Pinzhen  and Zhao, Zheng",
    booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
    month = jul,
    year = "2022",
    address = "Seattle, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.semeval-1.8",
    doi = "10.18653/v1/2022.semeval-1.8",
    pages = "75--81",
}