Code for Shrinking Embeddings for Hyper-relational Knowledge Graphs
B. Xiong, M. Nayyeri, S. Pan, und S. Staab. Software, (2024)Related to: Bo Xiong, Mojtaba Nayyeri, Shirui Pan, Steffen Staab. Shrinking Embeddings for Hyper-relational Knowledge Graphs. ACL 2023. arXiv: 2306.02199.
DOI: 10.18419/darus-3979
Zusammenfassung
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.
Related to: Bo Xiong, Mojtaba Nayyeri, Shirui Pan, Steffen Staab. Shrinking Embeddings for Hyper-relational Knowledge Graphs. ACL 2023. arXiv: 2306.02199
%0 Generic
%1 xiong2024shrinking
%A Xiong, Bo
%A Nayyeri, Mojtaba
%A Pan, Shirui
%A Staab, Steffen
%D 2024
%K darus ubs_10005 ubs_20008 ubs_30223 ubs_40506 unibibliografie
%R 10.18419/darus-3979
%T Code for Shrinking Embeddings for Hyper-relational Knowledge Graphs
%X 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.
@misc{xiong2024shrinking,
abstract = {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. },
added-at = {2024-07-08T09:47:31.000+0200},
affiliation = {Xiong, Bo/University of Stuttgart, Nayyeri, Mojtaba/University of Stuttgart, Pan, Shirui/Grififth University, Staab, Steffen/University of Stuttgart},
author = {Xiong, Bo and Nayyeri, Mojtaba and Pan, Shirui and Staab, Steffen},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2fa048d8866612cf1e8565ed6292fb352/unibiblio},
doi = {10.18419/darus-3979},
howpublished = {Software},
interhash = {6bc60d33d0ba9c13631ac703c842b1c6},
intrahash = {fa048d8866612cf1e8565ed6292fb352},
keywords = {darus ubs_10005 ubs_20008 ubs_30223 ubs_40506 unibibliografie},
note = {Related to: Bo Xiong, Mojtaba Nayyeri, Shirui Pan, Steffen Staab. Shrinking Embeddings for Hyper-relational Knowledge Graphs. ACL 2023. arXiv: 2306.02199},
orcid-numbers = {Xiong, Bo/0000-0002-5859-1961, Nayyeri, Mojtaba/0000-0002-9177-0312, Pan, Shirui/0000-0003-0794-527X, Staab, Steffen/0000-0002-0780-4154},
timestamp = {2025-03-10T11:20:35.000+0100},
title = {Code for Shrinking Embeddings for Hyper-relational Knowledge Graphs},
year = 2024
}