Uni-DUE Student Team: Tackling fact checking through decomposable attention neural network

12/27/2018
by   Jan Kowollik, et al.
0

In this paper we present our system for the FEVER Challenge. The task of this challenge is to verify claims by extracting information from Wikipedia. Our system has two parts. In the first part it performs a search for candidate sentences by treating the claims as query. In the second part it filters out noise from these candidates and uses the remaining ones to decide whether they support or refute or entail not enough information to verify the claim. We show that this system achieves a FEVER score of 0.3927 on the FEVER shared task development data set which is a 25.5

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/30/2020

Fact or Fiction: Verifying Scientific Claims

We introduce the task of scientific fact-checking. Given a corpus of sci...
research
10/15/2021

DialFact: A Benchmark for Fact-Checking in Dialogue

Fact-checking is an essential tool to mitigate the spread of misinformat...
research
04/16/2021

WhatTheWikiFact: Fact-Checking Claims Against Wikipedia

The rise of Internet has made it a major source of information. Unfortun...
research
09/03/2018

UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification

The Fact Extraction and VERification (FEVER) shared task was launched to...
research
09/30/2019

Automatic Fact-guided Sentence Modification

Online encyclopediae like Wikipedia contain large amounts of text that n...
research
12/24/2016

JU_KS_Group@FIRE 2016: Consumer Health Information Search

In this paper, we describe the methodology used and the results obtained...
research
08/30/2018

A Self-Attention Network for Hierarchical Data Structures with an Application to Claims Management

Insurance companies must manage millions of claims per year. While most ...

Please sign up or login with your details

Forgot password? Click here to reset