KBQA-BERT:基于知识图谱的QA系统，BERT模型-源码

[{"title":"（ 70 个子文件 5.79MB ） KBQA-BERT:基于知识图谱的QA系统，BERT模型-源码","children":[{"title":"KBQA-BERT-master","children":[{"title":"neo4j_qa.py <span style='color:#111;'> 834B </span>","children":null,"spread":false},{"title":"tf_metrics.py <span style='color:#111;'> 8.01KB </span>","children":null,"spread":false},{"title":"global_config.py <span style='color:#111;'> 2.00KB </span>","children":null,"spread":false},{"title":"lstm_crf_layer.py <span style='color:#111;'> 6.58KB </span>","children":null,"spread":false},{"title":"bert","children":[{"title":"run_squad.py <span style='color:#111;'> 45.29KB </span>","children":null,"spread":false},{"title":"multilingual.md <span style='color:#111;'> 10.54KB </span>","children":null,"spread":false},{"title":"tokenization.py <span style='color:#111;'> 10.31KB </span>","children":null,"spread":false},{"title":"run_classifier.py <span style='color:#111;'> 31.09KB </span>","children":null,"spread":false},{"title":"run_pretraining.py <span style='color:#111;'> 18.23KB </span>","children":null,"spread":false},{"title":"create_pretraining_data.py <span style='color:#111;'> 14.85KB </span>","children":null,"spread":false},{"title":"modeling.py <span style='color:#111;'> 37.28KB </span>","children":null,"spread":false},{"title":"tokenization_test.py <span style='color:#111;'> 4.28KB </span>","children":null,"spread":false},{"title":"requirements.txt <span style='color:#111;'> 110B </span>","children":null,"spread":false},{"title":"extract_features.py <span style='color:#111;'> 13.57KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"optimization_test.py <span style='color:#111;'> 1.68KB </span>","children":null,"spread":false},{"title":"optimization.py <span style='color:#111;'> 5.90KB </span>","children":null,"spread":false},{"title":"modeling_test.py <span style='color:#111;'> 8.98KB </span>","children":null,"spread":false},{"title":"CONTRIBUTING.md <span style='color:#111;'> 1.29KB </span>","children":null,"spread":false},{"title":"sample_text.txt <span style='color:#111;'> 4.29KB </span>","children":null,"spread":false},{"title":"LICENSE <span style='color:#111;'> 11.09KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 39.89KB </span>","children":null,"spread":false}],"spread":false},{"title":"kbqa_test.py <span style='color:#111;'> 7.29KB </span>","children":null,"spread":false},{"title":"run_ner.sh <span style='color:#111;'> 636B </span>","children":null,"spread":false},{"title":"terminal_ner.sh <span style='color:#111;'> 676B </span>","children":null,"spread":false},{"title":"Config","children":[{"title":"SIM","children":[{"title":"README.md <span style='color:#111;'> 123B </span>","children":null,"spread":false}],"spread":true},{"title":"NER","children":[{"title":"ner_data.conf <span style='color:#111;'> 155B </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 123B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"run_ner.py <span style='color:#111;'> 34.36KB </span>","children":null,"spread":false},{"title":"qa_my.sh <span style='color:#111;'> 661B </span>","children":null,"spread":false},{"title":"subpcs.py <span style='color:#111;'> 302B </span>","children":null,"spread":false},{"title":"run_similarity.py <span style='color:#111;'> 27.99KB </span>","children":null,"spread":false},{"title":"recommend_articles.log.2019-08-23 <span style='color:#111;'> 3.22MB </span>","children":null,"spread":false},{"title":"recommend_articles.log.2019-08-21 <span style='color:#111;'> 6.43MB </span>","children":null,"spread":false},{"title":"adcf.py <span style='color:#111;'> 3.14KB </span>","children":null,"spread":false},{"title":"fujc.py <span style='color:#111;'> 1.31KB </span>","children":null,"spread":false},{"title":"LICENSE <span style='color:#111;'> 11.09KB </span>","children":null,"spread":false},{"title":"terminal_predict.py <span style='color:#111;'> 15.09KB </span>","children":null,"spread":false},{"title":"recommend_articles.log.2019-08-06 <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"qa_my.py <span style='color:#111;'> 16.20KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 831B </span>","children":null,"spread":false},{"title":"Data","children":[{"title":"data_process.py <span style='color:#111;'> 3.12KB </span>","children":null,"spread":false},{"title":"construct_dataset.py <span style='color:#111;'> 1.98KB </span>","children":null,"spread":false},{"title":"load_dbdata.py <span style='color:#111;'> 3.30KB </span>","children":null,"spread":false},{"title":"Sim_Data","children":[{"title":"train.txt <span style='color:#111;'> 4.60MB </span>","children":null,"spread":false},{"title":"val.txt <span style='color:#111;'> 720.31KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 123B </span>","children":null,"spread":false},{"title":"dev.txt <span style='color:#111;'> 720.31KB </span>","children":null,"spread":false}],"spread":false},{"title":"DB_Data","children":[{"title":"README.md <span style='color:#111;'> 123B </span>","children":null,"spread":false},{"title":"clean_triple.csv <span style='color:#111;'> 1.13MB </span>","children":null,"spread":false}],"spread":false},{"title":"NER_Data","children":[{"title":"testing.txt <span style='color:#111;'> 1.06MB </span>","children":null,"spread":false},{"title":"train.txt <span style='color:#111;'> 1.52MB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 123B </span>","children":null,"spread":false},{"title":"dev.txt <span style='color:#111;'> 1.06MB </span>","children":null,"spread":false},{"title":"q_t_a_df_training.csv <span style='color:#111;'> 2.21MB </span>","children":null,"spread":false},{"title":"q_t_a_df_testing.csv <span style='color:#111;'> 1.51MB </span>","children":null,"spread":false}],"spread":false},{"title":"construct_dataset_attribute.py <span style='color:#111;'> 1.72KB </span>","children":null,"spread":false},{"title":"NLPCC2016KBQA","children":[{"title":"nlpcc-iccpol-2016.kbqa.training-data <span style='color:#111;'> 3.19MB </span>","children":null,"spread":false},{"title":"nlpcc-iccpol-2016.kbqa.kb <span style='color:#111;'> 29.15KB </span>","children":null,"spread":false},{"title":"nlpcc-iccpol-2016.kbqa.testing-data <span style='color:#111;'> 2.16MB </span>","children":null,"spread":false}],"spread":false},{"title":"triple_clean.py <span style='color:#111;'> 1.54KB </span>","children":null,"spread":false}],"spread":false},{"title":"image","children":[{"title":"NER.jpg <span style='color:#111;'> 11.10KB </span>","children":null,"spread":false},{"title":"KB.png <span style='color:#111;'> 15.46KB </span>","children":null,"spread":false}],"spread":false},{"title":"args.py <span style='color:#111;'> 786B </span>","children":null,"spread":false},{"title":"prt.py <span style='color:#111;'> 124B </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 1.17KB </span>","children":null,"spread":false},{"title":"kl.py <span style='color:#111;'> 42B </span>","children":null,"spread":false},{"title":"conlleval.pl <span style='color:#111;'> 12.52KB </span>","children":null,"spread":false},{"title":"his.py <span style='color:#111;'> 707B </span>","children":null,"spread":false},{"title":"conlleval.py <span style='color:#111;'> 9.97KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]