Atten-Bilstm relation pytorch 代码

# Att-BLSTM-relation-extraction [](https://paperswithcode.com/sota/relation-extraction-on-semeval-2010-task-8?p=attention-based-bidirectional-long-short-term) Implementation of [Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification](https://www.aclweb.org/anthology/P16-2034.pdf). ## Environment Requirements * python 3.6 * pytorch 1.3.0 ## Data * [SemEval2010 Task8](https://drive.google.com/file/d/0B_jQiLugGTAkMDQ5ZjZiMTUtMzQ1Yy00YWNmLWJlZDYtOWY1ZDMwY2U4YjFk/view?sort=name&layout=list&num=50) \[[paper](https://www.aclweb.org/anthology/S10-1006.pdf)\] * [glove.6B.100d.txt](https://nlp.stanford.edu/projects/glove/) ## Usage 1. Download the embedding and decompress it into the `embedding` folder. 2. Run the following the commands to start the program. ```shell python run.py ``` More details can be seen by `python run.py -h`. 3. You can use the official scorer to check the final predicted result. ```shell perl semeval2010_task8_scorer-v1.2.pl proposed_answer.txt predicted_result.txt >> result.txt ``` ## Result The result of my version and that in paper are present as follows: | paper | my version | | :------: | :------: | | 0.840 | 0.8313 | The training log can be seen in `train.log` and the official evaluation results is available in `result.txt`. *Note*: * Some settings may be different from those mentioned in the paper. * No validation set used during training. ## Reference Link