1. 利用网络上公开的数据构建一个小型的证券知识图谱(stock knowledge graph construction)
stock-knowledge-graph
2. 基于依存句法分析,面向开放域的实体和关系抽取(Chinese Open Entity Relation Extraction)
open-entity-relation-extraction
3. 基于多尺寸核卷积神经网络的关系抽取/分类(Relation Extraction via Convolutional Neural Network)
RE-CNN-pytorch
4. 基于Google AI的BERT模型实现中文命名实体识别(PyTorch solution of NER task Using Google AI's pre-trained BERT model.)
BERT-NER-pytorch
5. 图解NLP中的预训练模型(Graphical interpretation of the code, including Google AI's BERT, OpenAI's GPT.)
graphic-code
本文项目代码将持续更新。
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