Tracy: Tracing facts over knowledge graphs and text

Mohamed H. Gad-Elrab, Jacopo Urbani, Daria Stepanova, Gerhard Weikum

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

In order to accurately populate and curate Knowledge Graphs (KGs), it is important to distinguish s p o facts that can be traced back to sources from facts that cannot be verified. Manually validating each fact is time-consuming. Prior work on automating this task relied on numerical confidence scores which might not be easily interpreted. To overcome this limitation, we present Tracy, a novel tool that generates human-comprehensible explanations for candidate facts. Our tool relies on background knowledge in the form of rules to rewrite the fact in question into other easier-to-spot facts. These rewritings are then used to reason over the candidate fact creating semantic traces that can aid KG curators. The goal of our demonstration is to illustrate the main features of our system and to show how the semantic traces can be computed over both text and knowledge graphs with a simple and intuitive user interface.

Original languageEnglish
Title of host publicationThe Web Conference 2019
Subtitle of host publicationProceedings of The World Wide Web Conference WWW 2019
PublisherAssociation for Computing Machinery, Inc
Pages3516-3520
Number of pages5
ISBN (Electronic)9781450366748
DOIs
Publication statusPublished - 13 May 2019
Event2019 World Wide Web Conference, WWW 2019 - San Francisco, United States
Duration: 13 May 201917 May 2019

Conference

Conference2019 World Wide Web Conference, WWW 2019
CountryUnited States
CitySan Francisco
Period13/05/1917/05/19

Keywords

  • Explainable Evidence
  • Fact-checking
  • Knowledge Graph
  • Reasoning

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