BiBL

This is the repo for BiBL (Bidirectional Bayesian Learning).

Best Model Checkpoints

Checkpoints are available here: https://mega.nz/file/U2hn3ZJQ#2VFNjPOho7fXagWr0zX_8Rny7BIT7XtHYMSc5po0Pps

Instructions for Reproducing

We recommend using conda for dependency control.

Create conda ENV

conda create -n BIBL python=3.6
conda activate BIBL

Install spring-amr for general seq2seq formulation

cd BiBL
pip install -r requirements.txt
pip install -e .

Preparing datasets

Download AMR2.0 and AMR3.0 dataset from LDC for training. Place them right under the project folders and rename AMR2.0 dataset folder into amr2.0. (Keep the inner structure unchanged.)

Training

nohup ./sh/train_amr.sh & # lambda_g=0 + lambda_r=0 Text2AMR
nohup ./sh/train_text.sh & # lambda_g=0 + lambda_r=0 AMR2Text
nohup ./sh/train_amr-g_1-r_0_5.sh & # lambda_g=1.0 + lambda_r=0.5 Text2AMR
nohup ./sh/train_text-g_0_15-r_0_5.sh & # lambda_g=0.15 + lambda_r=0.5 AMR2Text

Best Checkpoints will be saved in "runs" folder.

Inference and Evaluation

Generate inference results for benchmark dataset

nohup ./predict_amr.sh & # please modify the model path and data generation path
nohup ./predict_text.sh & # please modify the model path and data generation path

Evaluation for Text2AMR

First we need to setup BLINK wiki entity linker. Please follow the instructions in https://github.com/facebookresearch/BLINK to complete the setup under BiBL project folder.

Then, blinkify the Text2AMR inference results.

nohup ./blinkify.sh & # please modify the BLINK model path

Finally, to have comparable Smatch scores with previous works, we need to use https://github.com/mdtux89/amr-evaluation for Smatch metric evaluation. Follow the instructions in amr-evaluation project to conduct the evaluation based on the blinkified results.

Evaluation for AMR2Text

First we need to setup jamr. Please follow the instructions in https://github.com/jflanigan/jamr to complete the setup under BiBL project folder.

nohup ./jamr_tokenize.sh & # please modify the jamr tokenizer script path
# please modify the generated inference data path & BLEU + chrF++ metrics will be generated
nohup ./eval_bleu.sh &
# please modify the generated inference data path & METEOR metrics will be generated
nohup ./eval_meteor.sh &