SO_with_CoVer

Code for 2023 ACL Findings Paper Sentence Ordering with a Coherence Verifier

Requirements

• python==3.8.10
• torch==1.13.0
• transformers==4.24.0
• dgl==0.9.1

Baselines

• BERSON: https://github.com/hwxcby/BERSON
• B-TSort: https://github.com/shrimai/Topological-Sort-for-Sentence-Ordering/

Data

For the AAN and NIPS data, please contact the authors of Sentence Ordering and Coherence Modeling using Recurrent Neural Networks.

The SIND dataset can be downloaded from the Visual Storytelling website.

And the ROCStory dataset can be download from here.

Code

CoVer

• Construct the instance with gradual permutation. Replace the specific name such as 'roc' with 'dataset'

python get_pairwise_hier_dataset.py dataset

• Train the model.

sh run_score.sh

B-TSort and BERSON with CoVer

If you already have the baseline B-TSort and BERSON model and a CoVer model, you can run run_rerank.sh in Topo_CoVer or run_{dataset}_coherence.sh in BERSON_CoVer.

Besides, we saved the pairwise scores generated by B-TSort in Topo_CoVer/pairwise_score, so that you can directly do the reranking process without having a B-TSort model.

Model

We provide the pretrained coherence model $CoVer$ and reproduced BERSON models for four datasets.

You can download from here: https://drive.google.com/drive/folders/1gHqH3inelArIDPhUIu8XjOAbXcaZSKok?usp=sharing