TY - JOUR

T1 - DeFacto - Temporal and multilingual deep fact validation

AU - Gerber, Daniel

AU - Esteves, Diego

AU - Lehmann, Jens

AU - Bühmann, Lorenz

AU - Usbeck, Ricardo

AU - Ngonga Ngomo, Axel Cyrille

AU - Speck, René

N1 - Publisher Copyright: © 2015 Elsevier B.V.

PY - 2015/12/1

Y1 - 2015/12/1

N2 - One of the main tasks when creating and maintaining knowledge bases is to validate facts and provide sources for them in order to ensure correctness and traceability of the provided knowledge. So far, this task is often addressed by human curators in a three-step process: issuing appropriate keyword queries for the statement to check using standard search engines, retrieving potentially relevant documents and screening those documents for relevant content. The drawbacks of this process are manifold. Most importantly, it is very time-consuming as the experts have to carry out several search processes and must often read several documents. In this article, we present DeFacto (Deep Fact Validation) - an algorithm able to validate facts by finding trustworthy sources for them on the Web. DeFacto aims to provide an effective way of validating facts by supplying the user with relevant excerpts of web pages as well as useful additional information including a score for the confidence DeFacto has in the correctness of the input fact. To achieve this goal, DeFacto collects and combines evidence from web pages written in several languages. In addition, DeFacto provides support for facts with a temporal scope, i.e., it can estimate in which time frame a fact was valid. Given that the automatic evaluation of facts has not been paid much attention to so far, generic benchmarks for evaluating these frameworks were not previously available. We thus also present a generic evaluation framework for fact checking and make it publicly available.

AB - One of the main tasks when creating and maintaining knowledge bases is to validate facts and provide sources for them in order to ensure correctness and traceability of the provided knowledge. So far, this task is often addressed by human curators in a three-step process: issuing appropriate keyword queries for the statement to check using standard search engines, retrieving potentially relevant documents and screening those documents for relevant content. The drawbacks of this process are manifold. Most importantly, it is very time-consuming as the experts have to carry out several search processes and must often read several documents. In this article, we present DeFacto (Deep Fact Validation) - an algorithm able to validate facts by finding trustworthy sources for them on the Web. DeFacto aims to provide an effective way of validating facts by supplying the user with relevant excerpts of web pages as well as useful additional information including a score for the confidence DeFacto has in the correctness of the input fact. To achieve this goal, DeFacto collects and combines evidence from web pages written in several languages. In addition, DeFacto provides support for facts with a temporal scope, i.e., it can estimate in which time frame a fact was valid. Given that the automatic evaluation of facts has not been paid much attention to so far, generic benchmarks for evaluating these frameworks were not previously available. We thus also present a generic evaluation framework for fact checking and make it publicly available.

KW - Fact validation

KW - NLP

KW - Provenance

KW - Web of Data

KW - Informatics

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=84948698827&partnerID=8YFLogxK

U2 - 10.1016/j.websem.2015.08.001

DO - 10.1016/j.websem.2015.08.001

M3 - Journal articles

AN - SCOPUS:84948698827

VL - 35

SP - 85

EP - 101

JO - Journal of Web Semantics

JF - Journal of Web Semantics

SN - 1570-8268

ER -