Replication Data for NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning (AAAI'24)

<p>This code is a PyTorch implementation of the paper "NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning (AAAI'24)".</p>

<p>NestE is a knowledge graph embedding method that can encode nested facts represented by quoted triples (h,r,t) in which the subject and object are triples themselves, e.g., ((BarackObama, holds_position, President), succeed_by, (DonaldTrump, holds_position, President)).</p>

<p>We implement six variant models of NetsE based on different hypercomplex number systems. NestE_Q.py for NestE with quaternion. NestE_H.py for NestE with hyperbolic quaternion. NestE_D.py for NestE with split quaternion. NestE_B.py, NestE_HB.py, and NestE_DB.py are the respective version with a translation component.</p>

<p>This code is used to reproduce the experiments of the paper. To execute the code, follow the instructions in the <a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=282636">README.md file</a>.</p>