# DocRed

**Repository Path**: zenglanllan/DocRed

## Basic Information

- **Project Name**: DocRed
- **Description**: 文档级别DocRed关系抽取
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-06-26
- **Last Updated**: 2022-10-27

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

## Code cloned from https://github.com/thunlp/DocRED/tree/master/code
# Baseline code

## Requirements and Installation
python3

pytorch>=1.0

```
pip3 install -r requirements.txt
```

## preprocessing data
Download metadata from [TsinghuaCloud](https://cloud.tsinghua.edu.cn/d/99e1c0805eb64736af95/) or [GoogleDrive](https://drive.google.com/drive/folders/1Ri3LIILKKBi3aBJjUVCOBpGX5PpONHRK) for baseline method and put them into prepro_data folder.


```
python3 gen_data.py --in_path ../data --out_path prepro_data
```

## relation extration

training:
```
CUDA_VISIBLE_DEVICES=0 python3 train.py --model_name BiLSTM --save_name checkpoint_BiLSTM --train_prefix dev_train --test_prefix dev_dev
```

testing (--test_prefix dev_dev for dev set, dev_test for test set):
```
CUDA_VISIBLE_DEVICES=0 python3 test.py --model_name BiLSTM --save_name checkpoint_BiLSTM --train_prefix dev_train --test_prefix dev_dev --input_theta 0.3601
```

## evaluation

dev result can evaluated by 
```
python3 evalutaion result.josn ../data/dev.json
```

test result should be submit to Codalab.