Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 63 tok/s
Gemini 2.5 Pro 49 tok/s Pro
GPT-5 Medium 14 tok/s Pro
GPT-5 High 19 tok/s Pro
GPT-4o 100 tok/s Pro
Kimi K2 174 tok/s Pro
GPT OSS 120B 472 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

R2RML and RML Comparison for RDF Generation, their Rules Validation and Inconsistency Resolution (2005.06293v1)

Published 13 May 2020 in cs.AI and cs.DB

Abstract: In this paper, an overview of the state of the art on knowledge graph generation is provided, with focus on the two prevalent mapping languages: the W3C recommended R2RML and its generalisation RML. We look into details on their differences and explain how knowledge graphs, in the form of RDF graphs, can be generated with each one of the two mapping languages. Then we assess if the vocabulary terms were properly applied to the data and no violations occurred on their use, either using R2RML or RML to generate the desired knowledge graph.

Citations (2)
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-Up Questions

We haven't generated follow-up questions for this paper yet.

Authors (1)