Tensorflow rlreReinforcement Learning for Relation Classification from Noisy Data(TensorFlow)
Stars: ✭ 150 (+257.14%)
AtnreAdversarial Training for Neural Relation Extraction
Stars: ✭ 108 (+157.14%)
GP-GNNCode and dataset of ACL2019 Paper: Graph Neural Networks with Generated Parameters for Relation Extraction.
Stars: ✭ 52 (+23.81%)
Rcnn Relation ExtractionTensorflow Implementation of Recurrent Convolutional Neural Network for Relation Extraction
Stars: ✭ 64 (+52.38%)
Att-BLSTM-relation-extractionImplementation of Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification.
Stars: ✭ 60 (+42.86%)
Hatt ProtoCode and dataset of AAAI2019 paper Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification
Stars: ✭ 149 (+254.76%)
CopymtlAAAI20 "CopyMTL: Copy Mechanism for Joint Extraction of Entities and Relations with Multi-Task Learning"
Stars: ✭ 97 (+130.95%)
Relation Classification Using Bidirectional Lstm TreeTensorFlow Implementation of the paper "End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures" and "Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths" for classifying relations
Stars: ✭ 167 (+297.62%)
JointreEnd-to-end neural relation extraction using deep biaffine attention (ECIR 2019)
Stars: ✭ 41 (-2.38%)
m3gmMax-Margin Markov Graph Models for WordNet (EMNLP 2018)
Stars: ✭ 40 (-4.76%)
Kg Baseline Pytorch2019百度的关系抽取比赛,使用Pytorch实现苏神的模型,F1在dev集可达到0.75,联合关系抽取,Joint Relation Extraction.
Stars: ✭ 149 (+254.76%)
limaThe Libre Multilingual Analyzer, a Natural Language Processing (NLP) C++ toolkit.
Stars: ✭ 75 (+78.57%)
Bertem论文实现(ACL2019):《Matching the Blanks: Distributional Similarity for Relation Learning》
Stars: ✭ 146 (+247.62%)
pynsettA programmable relation extraction tool
Stars: ✭ 25 (-40.48%)
ZhopenieChinese Open Information Extraction (Tree-based Triple Relation Extraction Module)
Stars: ✭ 98 (+133.33%)
Bert AttributeextractionUSING BERT FOR Attribute Extraction in KnowledgeGraph. fine-tuning and feature extraction. 使用基于bert的微调和特征提取方法来进行知识图谱百度百科人物词条属性抽取。
Stars: ✭ 224 (+433.33%)
Tre[AKBC 19] Improving Relation Extraction by Pre-trained Language Representations
Stars: ✭ 95 (+126.19%)
Ask2TransformersA Framework for Textual Entailment based Zero Shot text classification
Stars: ✭ 102 (+142.86%)
ExemplarAn open relation extraction system
Stars: ✭ 46 (+9.52%)
Pytorch Acnn Modelcode of Relation Classification via Multi-Level Attention CNNs
Stars: ✭ 170 (+304.76%)
RexREx: Relation Extraction. Modernized re-write of the code in the master's thesis: "Relation Extraction using Distant Supervision, SVMs, and Probabalistic First-Order Logic"
Stars: ✭ 21 (-50%)
R-BERTPytorch re-implementation of R-BERT model
Stars: ✭ 59 (+40.48%)
JointnreJoint Neural Relation Extraction with Text and KGs
Stars: ✭ 168 (+300%)
FoxFederated Knowledge Extraction Framework
Stars: ✭ 155 (+269.05%)
ReQuestIndirect Supervision for Relation Extraction Using Question-Answer Pairs (WSDM'18)
Stars: ✭ 26 (-38.1%)
R BertPytorch implementation of R-BERT: "Enriching Pre-trained Language Model with Entity Information for Relation Classification"
Stars: ✭ 150 (+257.14%)
knodleA PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.
Stars: ✭ 76 (+80.95%)
Open Ie PapersOpen Information Extraction (OpenIE) and Open Relation Extraction (ORE) papers and data.
Stars: ✭ 150 (+257.14%)
spertPyTorch code for SpERT: Span-based Entity and Relation Transformer
Stars: ✭ 572 (+1261.9%)
MacadamMacadam是一个以Tensorflow(Keras)和bert4keras为基础,专注于文本分类、序列标注和关系抽取的自然语言处理工具包。支持RANDOM、WORD2VEC、FASTTEXT、BERT、ALBERT、ROBERTA、NEZHA、XLNET、ELECTRA、GPT-2等EMBEDDING嵌入; 支持FineTune、FastText、TextCNN、CharCNN、BiRNN、RCNN、DCNN、CRNN、DeepMoji、SelfAttention、HAN、Capsule等文本分类算法; 支持CRF、Bi-LSTM-CRF、CNN-LSTM、DGCNN、Bi-LSTM-LAN、Lattice-LSTM-Batch、MRC等序列标注算法。
Stars: ✭ 149 (+254.76%)
CogIECogIE: An Information Extraction Toolkit for Bridging Text and CogNet. ACL 2021
Stars: ✭ 47 (+11.9%)
Information Extraction ChineseChinese Named Entity Recognition with IDCNN/biLSTM+CRF, and Relation Extraction with biGRU+2ATT 中文实体识别与关系提取
Stars: ✭ 1,888 (+4395.24%)
OpenUEOpenUE是一个轻量级知识图谱抽取工具 (An Open Toolkit for Universal Extraction from Text published at EMNLP2020: https://aclanthology.org/2020.emnlp-demos.1.pdf)
Stars: ✭ 274 (+552.38%)
BranFull abstract relation extraction from biological texts with bi-affine relation attention networks
Stars: ✭ 111 (+164.29%)
KGPool[ACL 2021] KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction
Stars: ✭ 33 (-21.43%)
Pytorch multi head selection reBERT + reproduce "Joint entity recognition and relation extraction as a multi-head selection problem" for Chinese and English IE
Stars: ✭ 105 (+150%)
HNREHierarchical Neural Relation Extraction
Stars: ✭ 93 (+121.43%)
ResideEMNLP 2018: RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information
Stars: ✭ 222 (+428.57%)
Distre[ACL 19] Fine-tuning Pre-Trained Transformer Language Models to Distantly Supervised Relation Extraction
Stars: ✭ 75 (+78.57%)
InformationExtractionSystemInformation Extraction System can perform NLP tasks like Named Entity Recognition, Sentence Simplification, Relation Extraction etc.
Stars: ✭ 27 (-35.71%)
Cnn Relation ExtractionTensorflow Implementation of Convolutional Neural Network for Relation Extraction (COLING 2014, NAACL 2015)
Stars: ✭ 203 (+383.33%)
BbwSemantic annotator: Matching CSV to a Wikibase instance (e.g., Wikidata) via Meta-lookup
Stars: ✭ 42 (+0%)
dialogreDialogue-Based Relation Extraction
Stars: ✭ 124 (+195.24%)
Marktool这是一款基于web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,同时也支持文本的迭代标注和实体的嵌套标注。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和调整,提高了标注语料的准确率和可靠性。
Stars: ✭ 190 (+352.38%)
FDDCNamed Entity Recognition & Relation Extraction 实体命名识别与关系分类
Stars: ✭ 29 (-30.95%)
VERSEVancouver Event and Relation System for Extraction
Stars: ✭ 13 (-69.05%)
Shukongdashi使用知识图谱,自然语言处理,卷积神经网络等技术,基于python语言,设计了一个数控领域故障诊断专家系统
Stars: ✭ 109 (+159.52%)
DocuNetCode and dataset for the IJCAI 2021 paper "Document-level Relation Extraction as Semantic Segmentation".
Stars: ✭ 84 (+100%)
Cnn Re TfConvolutional Neural Network for Multi-label Multi-instance Relation Extraction in Tensorflow
Stars: ✭ 190 (+352.38%)