Machine_reading_comprehension
machine reading comprehension with deep learning
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Nlp_paper_study | 3,373 | 9 months ago | 1 | C++ | ||||||
| 该仓库主要记录 NLP 算法工程师相关的顶会论文研读笔记 | ||||||||||
| Nlp Journey | 1,563 | 6 months ago | 3 | April 29, 2020 | apache-2.0 | Python | ||||
| Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc. All codes are implemented intensorflow 2.0. | ||||||||||
| Ner Bert | 404 | 4 years ago | n,ull | mit | Jupyter Notebook | |||||
| BERT-NER (nert-bert) with google bert https://github.com/google-research. | ||||||||||
| Marktool | 321 | 2 years ago | 6 | apache-2.0 | Vue | |||||
| DoTAT 是一款基于web、面向领域的通用文本标注工具，支持大规模实体标注、关系标注、事件标注、文本分类、基于字典匹配和正则匹配的自动标注以及用于实现归一化的标准名标注，同时也支持迭代标注、嵌套实体标注和嵌套事件标注。标注规范可自定义且同类型任务中可“一次创建多次复用”。通过分级实体集合扩大了实体类型的规模，并设计了全新高效的标注方式，提升了用户体验和标注效率。此外，本工具增加了审核环节，可对多人的标注结果进行一致性检验、自动合并和手动调整，提高了标注结果的准确率。 | ||||||||||
| Jointre | 39 | 5 years ago | 2 | other | Python | |||||
| End-to-end neural relation extraction using deep biaffine attention (ECIR 2019) | ||||||||||
| Nlp Experiments In Pytorch | 31 | 5 years ago | mit | Python | ||||||
| PyTorch repository for text categorization and NER experiments in Turkish and English. | ||||||||||
| Machine_reading_comprehension | 21 | 6 years ago | Python | |||||||
| machine reading comprehension with deep learning | ||||||||||
| Emr Ner | 19 | 6 years ago | 2 | Python | ||||||
| NER for Chinese electronic medical records. Use doc2vec, self_attention and multi_attention. | ||||||||||
| Defactonlp | 19 | 4 years ago | Python | |||||||
| DeFactoNLP: An Automated Fact-checking System that uses Named Entity Recognition, TF-IDF vector comparison and Decomposable Attention models. | ||||||||||
| Ner_demo | 17 | 4 years ago | Python | |||||||
| 中文命名实体识别NER。用keras实现BILSTM+CRF、IDCNN+CRF、BERT+BILSTM+CRF进行实体识别。结果当然是BERT+BILSTM+CRF最好啦。 | ||||||||||
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