WikiContradiction: Detecting Self-Contradiction Articles on Wikipedia

by   Cheng Hsu, et al.

While Wikipedia has been utilized for fact-checking and claim verification to debunk misinformation and disinformation, it is essential to either improve article quality and rule out noisy articles. Self-contradiction is one of the low-quality article types in Wikipedia. In this work, we propose a task of detecting self-contradiction articles in Wikipedia. Based on the "self-contradictory" template, we create a novel dataset for the self-contradiction detection task. Conventional contradiction detection focuses on comparing pairs of sentences or claims, but self-contradiction detection needs to further reason the semantics of an article and simultaneously learn the contradiction-aware comparison from all pairs of sentences. Therefore, we present the first model, Pairwise Contradiction Neural Network (PCNN), to not only effectively identify self-contradiction articles, but also highlight the most contradiction pairs of contradiction sentences. The main idea of PCNN is two-fold. First, to mitigate the effect of data scarcity on self-contradiction articles, we pre-train the module of pairwise contradiction learning using SNLI and MNLI benchmarks. Second, we select top-K sentence pairs with the highest contradiction probability values and model their correlation to determine whether the corresponding article belongs to self-contradiction. Experiments conducted on the proposed WikiContradiction dataset exhibit that PCNN can generate promising performance and comprehensively highlight the sentence pairs the contradiction locates.


page 1

page 6


WhatTheWikiFact: Fact-Checking Claims Against Wikipedia

The rise of Internet has made it a major source of information. Unfortun...

Analysing Temporal Evolution of Interlingual Wikipedia Article Pairs

Wikipedia articles representing an entity or a topic in different langua...

WikiSQE: A Large-Scale Dataset for Sentence Quality Estimation in Wikipedia

Wikipedia can be edited by anyone and thus contains various quality sent...

Automatic Fact-guided Sentence Modification

Online encyclopediae like Wikipedia contain large amounts of text that n...

Self-Supervised Claim Identification for Automated Fact Checking

We propose a novel, attention-based self-supervised approach to identify...

Extracting Core Claims from Scientific Articles

The number of scientific articles has grown rapidly over the years and t...

ReadNet: A Hierarchical Transformer Framework for Web Article Readability Analysis

Analyzing the readability of articles has been an important sociolinguis...

Please sign up or login with your details

Forgot password? Click here to reset