Neural relation extraction aims to extract relations from plain text with neural models, which has been the state-of-the-art methods for relation extraction. In this project, we provide our implementations of CNN [Zeng et al., 2014] and PCNN [Zeng et al.,2015] and their extended version with multi-lingual sentence-level attention scheme [Lin et al., 2017] .
We provide the dataset we used for the task relation extraction in (https://pan.baidu.com/s/1dF26l93). We preprocess the original data to make it satisfy the input format of our codes.
Pre-Trained English Word Vectors are learned from New York Times Annotated Corpus (LDC Data LDC2008T19), which should be obtained from LDC (https://catalog.ldc.upenn.edu/LDC2008T19).
Pre-Trained Chinese Word Vectors are learned from Chinese Baidu Baike (https://baike.baidu.com/).
To run our code, the dataset should be put in the folder data/ using the following format, containing six files
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train_en.txt / train_zh.txt: training file, format (wikidata_qid_e1, wikidata_qid_e2, e1_name, e2_name, relation, sentence).
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valid_en.txt / valid_zh.txt: validation file, same format as train.txt
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test_en.txt / test_zh.txt: test file, same format as train.txt.
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entity2id.txt: all entities and corresponding ids, one per line.
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relation2id.txt: all relations and corresponding ids, one per line.
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vec_en.bin, vec_zh.bin: the pre-train word embedding file
The source codes of various methods are put in the folders src/.
Just type "make" in the folder src/.
For training, you need to type the following command in each model folder:
./train
The training model file will be saved in folder out/ .
For testing, you need to type the following command in each model folder:
./test
The testing result which reports the precision/recall curve will be shown in pr.txt.
If you use the code, please cite the following paper:
[Lin et al., 2017] Yankai Lin, Zhiyuan Liu, and Maosong Sun. Neural Relation Extraction with Multi-lingual Attention. In Proceedings of ACL.[pdf]
[Zeng et al., 2014] Daojian Zeng, Kang Liu, Siwei Lai, Guangyou Zhou, and Jun Zhao. Relation classification via convolutional deep neural network. In Proceedings of COLING.
[Zeng et al.,2015] Daojian Zeng,Kang Liu,Yubo Chen,and Jun Zhao. Distant supervision for relation extraction via piecewise convolutional neural networks. In Proceedings of EMNLP.
[Lin et al., 2016] Yankai Lin, Shiqi Shen, Zhiyuan Liu, Huanbo Luan, and Maosong Sun. Neural Relation Extraction with Selective Attention over Instances. In Proceedings of ACL.[pdf]