A small knowledge graph (knowledge base) construction using data published on the web.
利用網絡上公開的數據構建一個小型的證券知識圖譜（知識庫）。
2. open-entity-relation-extraction
Knowledge triples extraction (entities and relations extraction) and knowledge base construction based on dependency syntax for open domain text.
基於依存句法分析，實現面向開放域文本的知識三元組抽取（實體和關系抽取）及知識庫構建。
參考：
- Chinese Open Relation Extraction and Knowledge Base Establishment (TALLIP 2018), Jia S et al. [paper]
3. RE-CNN-pytorch
Pytorch Implementation of Deep Learning Approach for Relation Extraction Challenge SemEval-2010 Task #8: Multi-Way Classification of Semantic Relations Between Pairs of Nominals via Convolutional Neural Network via Convolutional Neural Network with multi-size convolution kernels.
通過多尺寸卷積核卷積神經網絡的深度學習方法進行關系抽取/分類的PyTorch實現。
參考：
- Relation Classification via Convolutional Deep Neural Network (COLING 2014), D Zeng et al. [paper]
- Relation Extraction: Perspective from Convolutional Neural Networks (NAACL 2015), TH Nguyen et al. [paper]
4. BERT-NER-pytorch
PyTorch solution of Chinese Named Entity Recognition task with Google AI's BERT model.
利用Google AI的BERT模型進行中文命名實體識別任務的PyTorch實現。
參考：
- BERT: Pre-training of Deep Bidirectional Trasnsformers for Language Understanding (2018), Devlin et al. [paper]
5. technical-books
常用的技術書籍，內容主要涉及自然語言處理，機器學習，深度學習，算法，編程及數學等。
本文項目代碼將持續更新。
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