Abstract
The usefulness and usability of knowledge bases (KBs) is often limited by quality issues. One common issue is the presence of erroneous assertions, often caused by lexical or semantic confusion. We study the problem of correcting such assertions, and present a general correction framework which combines lexical matching, semantic embedding, soft constraint mining and semantic consistency checking. The framework is evaluated using DBpedia and an enterprise medical KB.
Highlights
Knowledge bases (KBs) such as Wikidata [42] and DBpedia [2] are playing an increasingly important role in applications such as search engines, question answering, common sense reasoning and data integration
We find that filtering with either link prediction (LP) or constraintbased validation (CV) can improve the correction rate when τ is set to a suitable range
As the empty rate is definitely increased after filtering, the accuracy for both DBP-Lit and MED-Ent is improved in the whole range of τ
Summary
Knowledge bases (KBs) such as Wikidata [42] and DBpedia [2] are playing an increasingly important role in applications such as search engines, question answering, common sense reasoning and data integration They still suffer from various quality issues, including constraint violations and erroneous assertions [11, 31], that negatively impact their usefulness and usability. We propose a method for correcting assertions whose objects are either erroneous entities or literals
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
