SNLP Fact Checker

Goal

Given a list of sentences test the correctness of each sentence

Method Overview

Extract Subject, Relation, Object triples from the input sentence
Find Wikipedia article of the extracted Subject
Parse Wikipedia Infobox of the Subject to extract Subject, Releation, Object triples
Compare Wikipedia triples against the input triples
Generate ttl file of results

Example

Input:

3347316	Nobel Peace Prize is Henry Dunant's honour.

Subject: "Henry Dunant" Object: "Nobel Peace Prize" Relation: "AWARD"
Related Wikipedia article: en.wikipedia.org/wiki/Henry_Dunant
Infobox:

Triples extracted from Wikipedia:
1. "Henry Dunant", "BORN_IN", "Geneva, Switzerland"
2. "Henry Dunant", "DIE_IN", "Heiden, Switzerland"
3. "Henry Dunant", "AWARD", "Nobel Peace Prize"
Comparing Input triple against Wikipedia triples yields the fact "Henry Dunant", "AWARD", "Nobel Peace Prize" is correct
Output 1.0 for this sentence
Output example

<http://swc2017.aksw.org/task2/dataset/3347316><http://swc2017.aksw.org/hasTruthValue>"1.0"^^<http://www.w3.org/2001/XMLSchema#double> .

Running the application

create a folder called data and put test.tsv file in this folder
set VM arguments as follows: -Xmx3060m -Dfile.encoding=UTF-8
run Main file de.upb.snlp.scm.Main
result.ttl file will be created in data folder
use conf.properties file to manage configuration (NER classifiers should be downloaded from nlp.stanford.edu)

Presentation

Presentation of the process

License