📖 A curated list of awesome resources dedicated to Relation Extraction, one of the most important tasks in Natural Language Processing (NLP).
Pytorch implementation of R-BERT: "Enriching Pre-trained Language Model with Entity Information for Relation Classification"
TensorFlow 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
code of Relation Classification via Multi-Level Attention CNNs
A PyTorch-based toolkit for natural language processing
Reinforcement Learning for Relation Classification from Noisy Data(TensorFlow)
Evaluating ChatGPT’s Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness
An Evaluation of ChatGPT on Information Extraction task, including Named Entity Recognition (NER), Relation Extraction (RE), Event Extraction (EE) and Aspect-based Sentiment Analysis (ABSA).
PyTorch-IE: State-of-the-art Information Extraction in PyTorch
Pytorch re-implementation of R-BERT model
Tensorflow Implementation of Recurrent Convolutional Neural Network for Relation Extraction
Relation Classification - SEMEVAL 2010 task 8 dataset
ACL 2019 paper:Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification
PyTorch implementation of relation extraction via convolutional neural network with multi-size convolution kernels.
This is a little Annotator tool using browser;这是一个基于浏览器运行的中文三元组(命名实体识别和关系分类)联合标注工具
Relation Classificaton based on information enhanced BERT
A curated list of awesome sentiment analysis studies, in which attitude corresponds to the text position conveyed by Subject towards other Object mentioned in text such as: entities, events, etc.
Convolution Neural Network for classification of semantic relations in a sentence
mul-BERT, the official score on the SemEval 2010 Task 8 dataset is up to 90.72 (Macro-F1).
Few-Shot Relation Extraction with AllenNLP
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