THU-KEG

Must-read papers on entity alignment published in recent years

THU-KEG

Entity Alignment toolkit (EAkit), a lightweight, easy-to-use and highly extensible PyTorch implementation of many entity alignment algorithms.

THU-KEG

Must-read papers on knowledge graph reasoning

THU-KEG

Source code for TACL paper "KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation".

THU-KEG

Source code and dataset for EMNLP 2020 paper "MAVEN: A Massive General Domain Event Detection Dataset".

THU-KEG

Source codes and datasets for EMNLP 2019 paper "Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot Relations"

THU-KEG

CCL2022 新闻脉络关系识别

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Source code for ACL 2021 paper "CLEVE: Contrastive Pre-training for Event Extraction"

THU-KEG

Source codes and datasets for EMNLP 2020 paper "Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph"

THU-KEG

Source code and datasets for EMNLP 2019 paper "Semi-supervised Entity Alignment via Joint Knowledge Embedding Model and Cross-graph Model".

THU-KEG