README.md

This repository contains the code for the paper:

"Covid vaccine is against Covid but Oxford vaccine is made at Oxford!" Semantic Interpretation of Proper Noun Compounds
Keshav Kolluru, Gabriel Stanovsky, Mausam
EMNLP 2022

Installation

Use the following commands to install the requirements required for running the code:

pip install -r requirements.txt
cd transformers
pip install --editable .
cd ..

Data

The data directory contains all the required files collected and used for the project.

Model Training

model_type= uniGen (or) clsGen
data= rand (or) nns
knowledge= base (or) sentence (or) knowledge_nnp (or) knowledge_nn (or) ner
seed=42

python run.py --model_name_or_path t5-base --output_dir models/${model_type}_${data}/${knowledge}/seed${seed} --overwrite_output_dir --do_predict --predict_with_generate --overwrite_cache --metric_type sacrebleu --num_train_epochs 10  --per_device_train_batch_size 16 --data_type ${data}_${knowledge} --model_type ${model_type} --seed ${seed}

Open IE Integration

bash openie_nci.sh

Citation

If you find the work useful, please consider citing our work

@inproceedings{kolluru22pronci,
    title = "{``}Covid vaccine is against Covid but {O}xford vaccine is made at {O}xford!{''} Semantic Interpretation of Proper Noun Compounds",
    author = "Kolluru, Keshav  and
      Stanovsky, Gabriel  and
      Mausam",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates",
    publisher = "Association for Computational Linguistics",    
}