piyushi-0/otalign

Repository of ACL2023 paper: Unbalanced Optimal Transport for Unbalanced Word Alignment

OTAlign: Optimal Transport based Monolingual Word Alignment

Prerequisite

• See src/requirements.txt
• Please collect word alignment datasets: MultiMWA, Edinburgh++, MSR-RTE
  • Place them in a data/ directory
  • Preprocessing codes for Edinburgh++ and MSR-RTE are in src/preprocess

Unsupervised Word Alignment

For details, please refer to the arguments in src/unsupervised_alignment.py

UN_OUTDIR=../out/unsupervised/
SEED=42
DATA=mtref
OT=uot
WT=uniform
DT=cos
$ python unsupervised_alignment.py --data $DATA --sure_and_possible --model bert-base-uncased --centering --pair_encode --layer -3 --out $UN_OUTDIR --ot_type $OT --weight_type $WT --dist_type $DT --seed $SEED

Supervised Word Alignment

For details, please refer to the arguments in src/supervised_alignment.py

Note Supervised word alignment uses hyperparameters estimated in the unsupervised setting. You first need to run unsupervised word alignment.

SU_OUTDIR=../out/supervised/
BATCH=64
PATIENCE=5

$ python python supervised_alignment.py --batch $BATCH --out $SU_OUTDIR --data $DATA --sure_and_possible --model bert-base-uncased --ot_type $OT --weight_type $WT --dist_type $DT --seed $SEED --patience $PATIENCE --unsupervised_dir $SU_OUTDIR

Citation

Please cite our ACL2023 paper if you use this repository:

Yuki Arase, Han Bao, and Sho Yokoi. Unbalanced Optimal Transport for Unbalanced Word Alignment, in Proc. of the Annual Meeting of the Association for Computational Linguistics (ACL 2023), (July 2023, to appear).

Contact

If you have any questions about codes in this repository, please contact Yuki Arase via email or simply post an issue 💬