LIKE THAT ONE TIME BEFORE IT'S ALL A MATTER OF PERSPECTIVE - FLORIAN PLÖTZKY BRAUNSCHWEIG, 06.07.2021 - IFIS
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Like that one time before… it’s all a matter of perspective Florian Plötzky Braunschweig, 06.07.2021
Previously at Erklärbär
Germany 2006
Charles Charles
Dempsey Dempsey
country year
recipient voter
„lead to“ Football World
Bribery caused Vote Cup 2006
Letter abstention
sender
Martin
Sonneborn
..
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 2
The many faces of events
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 3
What is an event?
• In this generality hard to say
• Mostly this definition fits for us:
– “something that happens at a given place and time
between a group of actors“ [SG16]
• However, this does not tell us much – how do
people work with events in computer science?
[SG16] Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 4
Event Communities
• Event Extraction
– How to practically extract events mostly from text
– Syntax-oriented
• Semantic web view
– How to model events with RDF and friends
– Semantic-oriented
• At least up to a certain degree…
– More later
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 5
Event Extraction
• How to extract events from text?
• Typically, event schemas are used
– Slot-based: each event has a number of participants
in certain roles; focused on the event participants
– Graph based: more focused on the relations
between event participants
• Can be constructed and filled from text or
derived from text in the first place (=event schema
induction)
[XW19], [LL+20] Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 6
Event Extraction: Event Schemas
Mostly generic in
nature, based on
what we can
express with
verbs.
Process view on
events (storyline
like). Bottom-up
approach
[XW19], [LL+20] Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 7
What about narratives?
Germany 2006
Charles Charles
Dempsey Dempsey
country year
recipient voter
„lead to“ Football World
Bribery caused Vote Cup 2006
Letter abstention
sender
Martin
Sonneborn
..
Event type: Event type:
Event type: bribery
vote abstention football world cup
Sender
Argument
Country
Argument
Role
Voter
Argument
Recipient
Role
Role
Year
Amount …
…
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 8
Semantic Models
• Where‘s a concept there‘s a conceptual model
from the semantic web community
– Let‘s focus on the simple event model (SEM)
[HM+11], [XW19] Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 9
Simple Sonneborn Model
sem:Actor sem:Actor
Type Type
rdf:type rdf:type
sem:Event
wordnet:recipient wordnet:sender
sem:actorType rdf:type sem:actorType
sem:hasActor sem:hasActor
wd:Q369030 ev:BriberyLetter wd:Q87485
rdfs:label rdfs:label
rdf:type rdf:type
„Charles Dempsey“ „Martin Sonneborn“
sem:Actor
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 10SEM usage 70km westward
• The EventKG (and to some degree the newer
OEKG) uses a variant to SEM to model a event
centric knowledge graph
• Applications:
– Event Timelines
– Spatio-temporal biographies
– In general SPARQL queries
–…
[ED18], [GK21+] Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 11Summary
• So, we can:
– Extract events on a syntactical level from text
(modulo errors as discussed by Hermann a few weeks
ago)
– Model events w.r.t. their participants (and roles),
space, time and relax some of the roles
– Use event-centric applications like time lines, sub
events to view a event on lower granularity, event
prediction (not covered here) and many more
• So where‘s the problem!?!
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 12Two thoughts on problems
P1
1. Are events in e.g. EventKG objectively
stored?
– Is there something like objective
observation or is it a question of
perspective?
– Who shot first?
1.
P2 If you explain an event like the Germany-
Brazil football game at the world cup
2014 there is more to it than „it was a
football game in Brazil in 2014 and the
participants have been Germany and
Brazil“, isn‘t it?
– How to compare events more
intelligently?
– What do you associate with the match?
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 13Who shot first? P1 Does it matter who shot first in Star Wars IV? Beside character building not really but … [HM+11] Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 14
Remember 2014 P1
• In 2014 Crimea become a part of the Russian
federation. Lets look at Wikipedia:
– The Crimean Peninsula, north of the Black Sea in Eastern Europe, was
annexed by the Russian Federation between February and March 2014 and
since then has been administered as two Russian federal subjects—the
Republic of Crimea and the federal city of Sevastopol. […] The Russian
government opposes the "annexation" label, with Putin defending
the referendum as complying with the principle of self-
determination of peoples.
Let‘s assume both sides (EU and Russia) are equally
credible for us, what does this sentence imply?
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 15Both lenses P1
The actual events of this complex event (or narrative?) are
the same but the event type changed…
1. Euromaidan protests 1. Euromaidan protests
2. Ukranian Revolution in Feb 2. Ukrainian Revolution in Feb
2014 2014
3. Russian Troops force 3. Crimean Referendum
Crimean Referendum 4. Secession of Crimea and
4. Annexion Crimea by Russia accession to Russia
Event Type: Annexion Event Type: Secession
Connotation: aggresive action of Connotation: Crimeans did not want
Russia, Ukraine as victim to stay, like the Scotland referendum in
2014
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 16And what‘s left… P1
• In Wikidata (and knowledge graphs in general) we
decouple the event from its views
– What‘s left is the annexation, the Russian viewpoint is
lost here
– This was also a critique when Wikidata was founded,
e.g. by the Atlantic author Mark Graham
[MG12] Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 17Stolen ideas P1 […] Look, for instance, at the Wikipedia pages about the Bronze Statue of Tallinn (a highly controversial moment in Estonia's history that sparked one of the world's first 'cyberwars' between Russia and Estonia). The Estonian and Russian versions of that article present interestingly different versions of the very same place and events. […] Not only does each language edition include different sets of topics, but when several editions do cover the same topic, they often put their own, unique spin on the topic. In particular, the ability of each language edition to exist independently has allowed each language community to contextualize knowledge for its audience. […] [MG12] Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 18
Non political example P1
Germany 2006
Charles Charles
Dempsey Dempsey
country year
recipient voter
„lead to“ Football World
Bribery caused Vote Cup 2006
Letter abstention
sender
Martin
Sonneborn
..
Felony? Satirical Action? Both? What’s the historical
viewpoint on such events?
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 19Take aways P1
• Events are always represented (or framed) through
the lenses of the narrator
– Depending on the lenses a concrete event may have n
types which may not compatible
– Moreover, downstream tasks like event prediction may be
dependent on the lenses for an event
• Taking advantage of this point may beneficial for
applications e.g. in the historical domain or for our
narrative quest
– Including an event with two potential types in a narrative
may determine the type w.r.t. to the remaining narrative…
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 20What‘s next P1
• Viewpoints me be seen as a special case of
context.
– I know, context is not solved yet
• Maybe a first step is to define what
metainformation we actually need to define a
viewpoint
– Next we need ways to represent, extract and evaluate
possible downstream tasks, and so on
• Subject of debate.
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 21It‘s like the time when we … P2
• Take this three events of the type ‘football match at
an international tournament’:
– E1: A few days ago in the football euro cup Switzerland
won against France in a penalty shootout
– E2: In 2004 Greece won the euro cup after beating
Portugal in the finals
– E3: In 2008 Spain won the euro cup after beating Germany
in the finals
• By now those three events would be treated as
‘similar’ or ‘comparable’ since they all have the same
types
– But are they?
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 22It‘s about perception P2
4:5 (3:3) 0:1
E1: In the round of 16 of the football E2: the EM was located in Portugal.
EM 2020 Switzerland beat France which Greece only once before entered the
was the current world champion at that KO stage of a tournament. Portugal had
time. Switzerland never reached the KO the better team and was the favorite.
stage of a football euro cup before and Still, Greece won.
won against all odds in a penalty
shootout.
0:1
E3: Germany successfully recovered at the
WM‘06 and faced a young and ambitious
Spanish team two years later. In the end
there was no clear favorite and Spain won.
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 23Enter analogies P2
• E2 might be used as an analogy on how to explain
E1.
– The underdog in this match won against the favorite
team
– This is a common pattern which we can relate to,
basically a David vs. Goliath situation
• How to describe and find them?
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 24What are analogies
• Cognitive process of transferring some high-level
meaning from one subject to another (base vs.
target) [CL13]
What you saw a few slides
before
[CL13] Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 25Analogy Theories
Structure Mapping Theory (SMT) High-Level Perception Theory
[DG83]
(HLT) [CF+92]
“An analogy is a comparison in which
Basically argues, that perceptive and
relational predicates, but few or no
cognitive processes can not be separated.
object attributes, can be mapped from
This adds to the notion, that also the
base to target.” [DG83]
view on different concepts plays a role
when trying to find a analogy between
SMT was introduced to explain the
base to target.
mechanisms on how to understand a
HLT vaguely tries to capture the notion
given analogy, but it can not produce new
of representation construction.
representations
[MD95], [DG83], [CF+92], [CL13] Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 264-way Analogies
• Typically 4-way analogies are used as a simplified
form to build and evaluate analogy-based information
systems
• However, this lead to some problems:
– Various analogies might not be mapped to a 4-way analogy
easily without losing the degree of similarity needed
– The aspects of HLT are lost, human percpetion and
abstractions are not involved in those kind of analogies
4-Way analogy:
Berlin ~ Germany like
Paris ~ France
[CL13], [LN13], [LA+16] Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 27What does it take P2
• Focus: analogies between events (not arbitrary
concepts)
• We need a necessity and sufficiency criterion to
define whether two events are analogous (or to
which degree / by which confidence they are)
– Plus: we need some hints on what to search during a
query. “Give me an event similar to GER-BRA in 2014”
will likely be a computational impossibility…
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 28N. Prototypes aka Plot Formulas P2
• Enter the narrative prototypes!
– Often mentioned before in different terms before at
the institute
– Similar to SMT, encode a small narrative which
represents a situation or archetype for an event
• E.g. the David vs. Goliath prototype mentioned before
• For this task context-sensitivity is useful
– If two events can be matched by the same prototype
it is likely to be an analogy
• Easier said than done …
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 29Example P2
SEM like notation for easier
Role:
underdog
depiction
in_role
participant winner ?X
?X
lead to Winning
confrontation
Ceremony
?Y participant
in_role
Role:
favorite
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 30Example (II)
Event Type: Football Match Event Type: Football Match
Participant 1 Switzerland Participant 1 Greece
Argument Role
Argument Role
Participant 2 France Participant 2 Portugal
Date 28.06.2021 Date 04.07.2004
Place Bucharest Place Lisbon
Winner Switzerland Winner Greece
Event Type: Football Match
Participant 1 Germany
Argument Role
Participant 2 Spain
Date 29.06.2008
Place Vienna
Winner Spain
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 31MatchIT… finally P2
Event Type: Football Match
Participant 1 Switzerland
Argument Role
Participant 2 France
Date 28.06.2021
Place Bucharest
Winner Switzerland
How to determine, if the
role label is suitable?
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 32Thoughts on roles P2
• The semantic of the roles depend on the event
type and the relation between the event
participants
– ?Y must be stronger than ?X in an confrontation event
– ‘Stronger’ is herby defined by the context spanned by
the event type
• E.g. the total worthiness of the team, a current title (like
world cup champion), win:lose ratio at the tournament etc.
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 33Thoughts on roles P2
• So the context of an entity type defines the
attributes for a role which can then be used to define
a role function
– E.g. R(?X, ?Y, ‚underdog‘, ‚favorite‘, ‚football match‘) which
yields a confidence value whether isUnderdog(?X, ?Y) &&
isFavorite(?Y, ?X) w.r.t. ‚football match‘
• E.g. R(‚Switzerland‘, ‚France‘, ‚underdog‘, ‚favorite‘, ‚EM 2020‘)
– This function is not commutative!
• May also be approximated by using the role labels
and the country and exploiting the distributional
hypothesis or something similar?
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 34Finalize the Example P2
Necessity: Mapping
from the event
schema
Sufficiency: The R(‚Switzerland‘, ‚France‘, ‚underdog‘, ‚favorite‘, ‚EM 2020‘)=1
R(‚Germany‘, ‚Spain‘, ‚underdog‘, ‚favorite‘, ‚EM 2008‘)=0.2
role labels fit R(‚Greece‘, ‚Portugal‘, ‚underdog‘, ‚favorite‘, ‚EM 2004‘)=1
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 35Connecting the dots
• The matching problem between the prototypes
and event schemas may follow the SMT
– We have to decide which relations are important to
build the analogy
• What about the role labeling?
– Was Switzerland the underdog? …. Here P1 comes
into play
• If we know the perception regarding a role we may use it in
building the analogies from P2
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 36Vision (no picture, sorry)
• A portion of an analogous information system
dealing with events
time before … perspective
Like that one it’s all a matter of
– Allows for analogy queries (P2) by using narrative
prototypes generated by users and role
perspectives given by the user or collected in P1
– Enriches raw event schemas by perspective
information to allow for viewpoints as discussed
in P1
• Already existing KGs like EventKG may be used. The
perspectives may be attached by using extracting it
from text or by asking language models (with all
nitpicks …)
• More to come!
– But not today
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig 37The end (you can wake up now)
ploetzky@ifis.cs.tu-bs.de
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig, Germany 38References
− [CF+92] Chalmers, D. J., French, R. M., & Hofstadter, D. R. (1992). High-level perception, representation, and analogy: A
critique of artificial intelligence methodology. Journal of Experimental & Theoretical Artificial Intelligence, 4(3), 185-211.
− [CL13] Lofi, C. (2013). Analogy Queries in Information Systems—A New Challenge. Journal of Information & Knowledge
Management, 12(03), 1350021.
− [DG83] Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive science, 7(2), 155-170.
− [GD18] Gottschalk, S., & Demidova, E. (2018). Eventkg: A multilingual event-centric temporal knowledge graph. In ESWC.
− [GK+21] Gottschalk, S., Kacupaj, E., Abdollahi, S., Alves, D., Amaral, G., Koutsiana, E., ... & Thakkar, G. (2021). OEKG: The
Open Event Knowledge Graph. In CLEOPATRA@WWW.
− [HM+11] Van Hage, W. R., Malaisé, V., Segers, R., Hollink, L., & Schreiber, G. (2011). Design and use of the Simple Event Model
(SEM). Journal of Web Semantics, 9(2), 128-136.
− [LA+16] Lofi, C., Ahamed, A., Kulkarni, P., & Thakkar, R. (2016). Benchmarking semantic capabilities of analogy querying
algorithms. In DASFAA.
− [LN13] Lofi, C., & Nieke, C. (2013). Modeling analogies for human-centered information systems. In SocInfo.
− [LL+20] Li, M., Zeng, Q., Lin, Y., Cho, K., Ji, H., May, J., ... & Voss, C. (2020). Connecting the dots: Event graph schema induction
with path language modeling. In EMNLP.
− [MD95] Morrison, C. T., & Dietrich, E. (1995). Structure-mapping vs. high-level perception: The mistaken fight over the
explanation of analogy. In Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society.
− [MG12] Graham, M. (2012). The Problem With Wikidata. The Atlantic. URL:
https://www.theatlantic.com/technology/archive/2012/04/the-problem-with-wikidata/255564/
− [SG16] Spitz, A., & Gertz, M. (2016). Terms over LOAD: leveraging named entities for cross-document extraction and
summarization of events. In SIGIR.
− [XW19] Xiang, W., & Wang, B. (2019). A survey of event extraction from text. IEEE Access, 7, 173111-173137.
Florian Plötzky – Institut für Informationssysteme – TU Braunschweig, Germany 39You can also read
