Code for Shrinking Embeddings for Hyper-relational Knowledge Graphs

DOI

This is a Pytorch implementation of the paper Shrinking Embeddings for Hyper-relational Knowledge Graphs published in ACL'23.

This code is used to reproduce the experiments of the method ShrinkE, a geometric embedding approach for hyper-relational knowledge graphs. The code is implemented with Python 3 and pytorch. The code is tested on public datasets which can be download from StarE. To execute the code, follow the instructions in the README.md file.

For more info, please check the paper or feel free to contact the authors for any inquiries.

Further information can be found in the README.md.

Identifier
DOI https://doi.org/10.18419/darus-3979
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/darus-3979
Provenance
Creator Xiong, Bo ORCID logo; Nayyeri, Mojtaba ORCID logo; Pan, Shirui (ORCID: 0000-0003-0794-527X); Staab, Steffen ORCID logo
Publisher DaRUS
Contributor Xiong, Bo; Staab, Steffen
Publication Year 2024
Funding Reference European Commission info:eu-repo/grantAgreement/EC/H2020/860801
Rights MIT License; info:eu-repo/semantics/openAccess; https://spdx.org/licenses/MIT.html
OpenAccess true
Contact Xiong, Bo (Universität Stuttgart); Staab, Steffen (Universität Stuttgart)
Representation
Resource Type Dataset
Format application/octet-stream; text/x-python; text/plain; charset=US-ASCII; application/x-ipynb+json; text/markdown; text/plain
Size 6092; 6071; 8582; 6320; 7117; 8382; 8658; 14109; 2008; 11115; 11099; 13698; 1002; 7677; 20997; 123; 130; 125; 132; 0; 3152; 1071; 56814; 58397; 71267; 6510; 13045; 13607; 83504; 5011; 15674; 18783; 95155; 1765498; 656; 113; 13190; 3868; 3490; 6998; 9687
Version 1.0
Discipline Other