gaomin0806's starred repositories

DRKG

A knowledge graph and a set of tools for drug repurposing

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bertviz

BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

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word-embedding-dimensionality-selection

On the Dimensionality of Word Embedding

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SJTUThesis

上海交通大学 LaTeX 论文模板 | Shanghai Jiao Tong University LaTeX Thesis Template

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LGN

EMNLP-2019 paper: A Lexicon-based Graph Neural Network for Chinese NER.

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kg-bert

KG-BERT: BERT for Knowledge Graph Completion

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GraphLSTM_release

Implementation of TACL 2017 paper: Cross-Sentence N-ary Relation Extraction with Graph LSTMs. Nanyun Peng, Hoifung Poon, Chris Quirk, Kristina Toutanova and Wen-tau Yih.

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pubmed_parser

:clipboard: A Python Parser for PubMed Open-Access XML Subset and MEDLINE XML Dataset

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OpenKE

An Open-Source Package for Knowledge Embedding (KE)

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TensorFlow-TransX

An implementation of TransE and its extended models for Knowledge Representation Learning on TensorFlow

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nalaf

NLP framework in python for entity recognition and relationship extraction

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TCN

Sequence modeling benchmarks and temporal convolutional networks

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FewRel

A Large-Scale Few-Shot Relation Extraction Dataset

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pytorch_graph-rel

A PyTorch implementation of GraphRel

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WordGCN

ACL 2019: Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks

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LatticeLSTM

Chinese NER using Lattice LSTM. Code for ACL 2018 paper.

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DocRED

Dataset and codes for ACL 2019 DocRED: A Large-Scale Document-Level Relation Extraction Dataset.

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Chinese_NRE

Source code for ACL 2019 paper "Chinese Relation Extraction with Multi-Grained Information and External Linguistic Knowledge"

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multi-embedding-cws

Multiple Character Embeddings for Chinese Word Segmentation, ACL 2019

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Radical_CR_Encoder

Chinese Orthographic Units-based Text Encoder (Radical Embedding)

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Chinese-clinical-NER

CCKS2019中文命名实体识别任务。从医疗文本中识别疾病和诊断、解剖部位、影像检查、实验室检验、手术和药物6种命名实体。现已实现基于jieba和AC自动机的baseline构建、基于BiLSTM和CRF的序列标住模型构建。bert的部分代码主要源于https://github.com/charles9n/bert-sklearn.git 感谢作者。 模型最终测试集得分0.81,还有较大改进空间。可以当做一个baseline。

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ccks2019

实体识别比赛

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ccks_baidu_entity_link

ccks baidu entity link 实体链接 第一名

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ccks2019_el

CCKS 2019 Task 2: Entity Recognition and Linking

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CCKScner

CCKS2019 面向中文电子病历的命名实体识别

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s800

Tools for working with the S800 corpus

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standoff2conll

Conversion from brat-flavored standoff to CoNLL format

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Chinese-Word-Vectors

100+ Chinese Word Vectors 上百种预训练中文词向量

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ERNIE

Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.

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