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This repo contains code for the EMNLP 2021 paper:

Is Everything in Order? A Simple Way to Order Sentences

Somnath Basu Roy Chowdhury*, Faeze Brahman*, Snigdha Chaturvedi EMNLP 2021

Link to paper

Please create a fresh conda env and run:

pip install -r requirements.txt

First, create the dataset splits and put them in ./data folder.

Please find the links for the various datasets: arXiv, Wiki Movie Plots, SIND, NSF, ROCStories, NeurIPS, AAN.

All datsets should be formatted in jsonl files where each line is a json containing two fields: orig_sents, and shuf_sents. orig_sents is a list of markers [y1, y2, ..., yN], which denotes the position of ith sentence of the corresponding ordered sequence in the shuffled input (shuf_sents). An example is provided for ROCStories in here.

To train the ReBART model run the following command:

bash train_rebart.sh

You can specify the hyper-parameters inside the bash script.

To generate the outputs (position markers) using the trained model, run the following commands:

export DATA_DIR="data/arxiv-abs"
export MODEL_PATH="outputs/reorder_exp/bart-large_arxiv"
python source/generate.py --in_file $DATA_DIR/test.jsonl --out_file $MODEL_PATH/test_bart_greedy.jsonl --model_name_or_path $MODEL_PATH --beams 1 --max_length 40 --task index_with_sep --device 0

To evaluate the model and get the performance metrics, run:

python eval/evaluation.py --output_path $MODEL_PATH/test_bart_greedy.jsonl

If you used our work please cite us using:

@inproceedings{Basu-brahman-chaturvedi-rebart,
    title = "Is Everything in Order? A Simple Way to Order Sentences",
    author = "Somnath Basu Roy Chowdhury, Faeze Brahman and
      Snigdha Chaturvedi",
    booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    month = nov,
    year = "2021",
    publisher = "Association for Computational Linguistics",
}