/NRE-Q

Neural Relation Extraction Method with Specific Docs.(Now for PCNN model)

Primary LanguagePerl

NRE-Q Project

The mainly purpose of starting this project is to build simple & readable deep learning neural relation extraction tutorials for beginners who want to study natural language processing.

This project is organized clearly.

  • Models are stored in ./models folder. You can still find descriptions of models in ./models folder.

  • Dataset contains all various common RE dataset. - E.g. dataset/sem-task8 is one of RE dataset, and all original dataset files are contained in dataset/sem-task8 folder directly. In dataset/sem-task8 you can still finds dataset/sem-task8/train, dataset/sem-task8/test , they are generated by dataset/semProcessor.py to build the SEMData, a subclass of torch.utils.data.Dataset, which used to build dataLoader.

  • Checkpoints : used to record your best model parameters, which is now a empty folder.

  • source : store all images used in README.md

  • semeval : contains evaluate func which is provide by official dataset owner, details are showed in semeval/README.md.

  • config.py : to test all provide model in this project, all you need is to change this file. contains which model you want to train & all parameters you can tunes.

  • main.py : contains iterations on train & test dataset, and generate result.txt into semeval dataset.