WGSUM

Code for findings of ACL 2021 paper: [Word Graph Guided Summarization for Radiology Findings]

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This repo contains the code following PreSumm

Requirements

• Python 3 (tested on 3.7)
• PyTorch (tested on 1.5)

Data

We give an example about the data in the graph_construction/.

Preparation

Remain to be origanized. Some of the code needs to be debug, plz use it carefully.

Graph Construction

We have given the example about the data format to construct the graph (each line is a radiology report). You might need to change the data path to you own data path.

cd graph_construction
python graph_construction.py

After finish graph construction. need to run sh precess_radiology.sh to further process data. For this step, you can obtain more information from the link (https://github.com/nlpyang/PreSumm). Note that you also need to change the 322-324 row in src/prepro/data_builder.py to your own data.

Training

change DATA_PATH to your data_path To start training, run

sh WGSUM_Trans.sh

Evaluation

change DATA_PATH Model_path to your data_path and model path To start evaluation, run

sh WGSUM_test.sh

Pre-trained model

you can download the pre-trained models from (the link passwd: f2bl) or from the link