Search Results for author: Christian Meilicke

Found 8 papers, 2 papers with code

On Aligning OpenIE Extractions with Knowledge Bases: A Case Study

no code implementations EMNLP (Eval4NLP) 2020 Kiril Gashteovski, Rainer Gemulla, Bhushan Kotnis, Sven Hertling, Christian Meilicke

First, we investigate OPIEC triples and DBpedia facts having the same arguments by comparing the information on the OIE surface relation with the KB rela- tion.

Open Information Extraction

SAFRAN: An interpretable, rule-based link prediction method outperforming embedding models

1 code implementation AKBC 2021 Simon Ott, Christian Meilicke, Matthias Samwald

SAFRAN yields new state-of-the-art results for fully interpretable link prediction on the established general-purpose benchmarks FB15K-237, WN18RR and YAGO3-10.

Knowledge Graphs Link Prediction

Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphs

1 code implementation10 Dec 2020 Simon Ott, Laura Graf, Asan Agibetov, Christian Meilicke, Matthias Samwald

SAFRAN yields new state-of-the-art results for fully interpretable link prediction on the established general-purpose benchmark FB15K-237 and the large-scale biomedical benchmark OpenBioLink.

Knowledge Graphs Link Prediction

On Evaluating Embedding Models for Knowledge Base Completion

no code implementations WS 2019 Yanjie Wang, Daniel Ruffinelli, Rainer Gemulla, Samuel Broscheit, Christian Meilicke

In this paper, we explore whether recent models work well for knowledge base completion and argue that the current evaluation protocols are more suited for question answering rather than knowledge base completion.

Knowledge Base Completion Question Answering

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