Revisiting Evaluation of Knowledge Base Completion Models

Pouya Pezeshkpour
Pouya Pezeshkpour
Yifan Tian
Yifan Tian

AKBC, 2020.

Cited by: 0|Bibtex|Views8|DOI:https://doi.org/10.24432/C53S3W
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Other Links: academic.microsoft.com|dblp.uni-trier.de

Abstract:

Representing knowledge graphs (KGs) by learning embeddings for entities and relations has led to accurate models for existing KG completion benchmarks. However, due to the open-world assumption of existing KGs, evaluation of KG completion uses ranking metrics and triple classification with negative samples, and is thus unable to directly ...More

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