1.
Building Event-Centric Knowledge
Graphs from News
Marco Rospocher, Marieke van Erp, Piek Vossen, Antske Fokkens, Itziar
Aldabe, German Rigau, Aitor Soroa, Thomas Ploeger, Tessel Bogaard
http://www.newsreader-project.eu

2.
Event-Centric Knowledge Graphs (ECKGs)
• An ECKG represents changes in the world
• Can capture long-term developments and histories of
entities
• Complementary to (static) encyclopaedic information
found in (entity-centric) knowledge-graphs

3.
Why ECKGs?
• Policy makers and information specialists need to know
what’s happening/what’s happened to an entity
• Current de facto standard is Google/Information broker
document-based search
• A ‘database’ of events would make their work easier
• Carried out as part of the NewsReader project Jan 2013 -
Dec 2015 (EU FP7 project)
• http://www.newsreader-project.eu

4.
Processing Pipeline
Step 1: Information Extraction at the Document Level
Step 2: Cross-
document event
coreference
opinion miner
word sense
disambiguation
multiwords
tagger
syntactic
parser
tokenizer
part-of-speech
tagger
named entity
recognizer
named entity
disambiguation
nominal
coreference
resolution
semantic role
labeler
event
coreference
resolution
time and date
recognition
Porsche family buys back 10pc stake from Qatar
Descendants of the German car pioneer Ferdinand Porsche
have bought back a 10pc stake in the company that bears the
family name from Qatar Holding, the investment arm of the Gulf
State’s sovereign wealth fund.
All of the common shares in Porsche Automobil Holding SE are
now held by the Porsche-Piech family, descendants of the eng-
17/06/2013
Qatar Holding sells 10% stake in Porsche to
founding families
Qatar Holding, the investment arm of the Gulf state’s sovereign
wealth fund, has sold its 10 percent stake in Porsche SE to the
luxury carmaker’s family shareholders, four years after it first
invested in the firm.
Qatar Holding, which owns stakes in some of the world’s
largest companies, said it sold the common shares in the
automaker to the Porsche and Piech families. It did not
disclose the value of the transaction.
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix time: <http://www.w3.org/TR/owl-time#> .
@prefix eso: <http://www.newsreader-project.eu/domain-ontology#> .
@prefix gaf: <http://groundedannotationframework.org/gaf#> .
@prefix nwrontology: <http://www.newsreader-project.eu/ontologies/> .
@prefix sem: <http://semanticweb.cs.vu.nl/2009/11/sem/> .
@prefix fn: <http://www.newsreader-project.eu/ontologies/framenet/> .
<http://www.newsreader-project.eu/instances> {
<http://www.telegraph.co.uk#ev2>
a sem:Event , fn:Commerce_buy , eso:Buying ;
rdfs:label "buy" , "sell";
gaf:denotedBy <http://www.telegraph.co.uk#char=15,19> , <http://english.alarabiya.net#char=14,19> .
<http://dbpedia.org/resource/Porsche>
rdfs:label "Porsche" , "founding family" ;
gaf:denotedBy <http://www.telegraph.co.uk#char=0,7> , <http://english.alarabiya.net#char=33,40> , <http://english.alarabiya.net#char=44,61> .
<http://www.newsreader-project.eu/data/cars/non-entities/10pc+stake>
rdfs:label "10pc stake", "10 % stake in Porsche" ;
gaf:denotedBy <http://www.telegraph.co.uk#char=25,35>, <http://english.alarabiya.net#char=20,40> .
<http://dbpedia.org/resource/Qatar>
<?xml version="1.0"
encoding="UTF-8"
standalone="yes"?>
<NAF version="v3"
xml:lang="en">
<nafHeader>
<fileDesc
creationtime="20130617"/>
<public uri="5BC0-9GD1-
F0JP-W2H2.xml"/>
<linguisticProcessors
layer="srl">
<lp name="ixa-pipe-srl-en"
timestamp="2014-02-58T19:28:
32+0100" version="1.0"/>
temporal
relation
extraction
causal relation
extraction
factuality
detection
event
coreference
resolution
<?xml version="1.0"
encoding="UTF-8"
standalone="yes"?>
<NAF version="v3"
xml:lang="en">
<nafHeader>
<fileDesc
creationtime="20130617"/>
<public uri="5BC0-9GD1-
F0JP-W2H2.xml"/>
<linguisticProcessors
layer="srl">
<lp name="ixa-pipe-srl-en"
timestamp="2014-02-58T19:28:
32+0100" version="1.0"/>

5.
NLP Pipeline
• State-of-the-art pipeline
• English, Spanish, Italian & Dutch
• ‘Black box’ setup and individual modules available from:
http://www.newsreader-project.eu/results/software/
• All modules take NAF as input and output NAF

6.
NLP Pipeline output

7.
Cross-Lingual Event Extraction

8.
Cross-Lingual Event Extraction

9.
Text2RDF

10.
Event and Situation Ontology (ESO)

11.
Event and Situation Ontology (ESO)
See also: P. Vossen, R. Agerri, I. Aldabe, A. Cybulska, M. van Erp, A. Fokkens, E. Laparra, A. Minard, A. P. Aprosio, G. Rigau, M. Rospocher, and R. Segers,
“NewsReader: How Semantic Web Helps Natural Language Processing Helps Semantic Web,” Special issue Knowledge-Based Systems, Elsevier, 2016.

12.
Resulting ECKGs

13.
Resulting ECKGs
P. Vossen, R. Agerri, I. Aldabe, A. Cybulska, M. van Erp, A. Fokkens, E. Laparra, A. Minard, A. P. Aprosio, G. Rigau, M. Rospocher, and R. Segers,
“NewsReader: How Semantic Web Helps Natural Language Processing Helps Semantic Web,” Special issue Knowledge-Based Systems, Elsevier, 2016.

14.
ECKG Quality Evaluation
• Random sample of 100 Events from Wikinews
• 4 groups of 25 events (~260 triples), each evaluated by 2
human raters
• Strict co-reference evaluation; if an event had 4 mentions of
which 3 were correct, all coreference triples were considered
incorrect

15.
Applications: Query for Occurrences per Year

16.
Applications: Network

17.
Applications: Interactive Visualisation

18.
Conclusions
• ECKGs capture “who”, “what”, “where”, “when”
• Deep NLP techniques can be used to extract events from
large amounts of text
• Distinguishing between mentions and instances allows
for cross-lingual event extraction through semantic layer
(no MT needed)
• ECKGs were evaluated and tested in hackathons

19.
Current & Future Work
• Adapting the tools to the humanities domain for
• Working on capturing perspectives (QuPiD2) and
storylines (ULM-3)
• Your domain/project? Get in touch:
marieke.van.erp@vu.nl

20.
Play with the Wikinews ECKG at:
https://knowledgestore.fbk.eu/
Code and documentation at:
http://www.newsreader-project.eu/results/software/

21.
NewsReader was funded by the European Union’s 7th Framework
Programme (ICT-316404)
This work is continued with support from the CLARIAH-CORE
project financed by NWO