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Data · dataset · 2024

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

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

Description

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)). 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.

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NestE_B.py, NestE_HB.py, and NestE_DB.py are the respective version with a translation component. This code is used to reproduce the experiments of the paper. To execute the code, follow the instructions in the README.md file.

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Where it is published

Catalogue records · 1

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Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
DaRUSdoi:10.18419/DARUS-397812 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:field:460206enrichment · darus uni stuttgart detaxonomy-embedding@1.1.0title+keywords+description (76%)
concepts[field].dataverse_subject:computer-and-information-sciencesource · darus uni stuttgart deconnector:darus_uni_stuttgart_de@1.0.0/subjects
created_datesource · darus uni stuttgart deconnector:darus_uni_stuttgart_de@1.0.0
descriptionsource · darus uni stuttgart deconnector:darus_uni_stuttgart_de@1.0.0/description
publication_datesource · darus uni stuttgart deconnector:darus_uni_stuttgart_de@1.0.0
titlesource · darus uni stuttgart deconnector:darus_uni_stuttgart_de@1.0.0/name
updated_datesource · darus uni stuttgart deconnector:darus_uni_stuttgart_de@1.0.0
version_labelsource · darus uni stuttgart deconnector:darus_uni_stuttgart_de@1.0.0