timo honkela: semantic and pragmatics representations of large text corpora

Timo Honkela, FIN-CLARIN Jubilee seminar, 9.6.2016

Timo Honkela

FIN-CLARIN Jubilee Seminar andNordic CLARIN Network SeminarUniversity of Helsinki, 9 Jun 2016

Semantic and pragmatic representations

of large text corpora

[email protected]

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Agenda

● Digital humanities in Finland● Strategic role of humanities and

social sciences● Research using text corpora

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Digital humanities in Finland

● Research in humanities and social sciences is increasingly using digitally stored resources and computational analysis tools


Krister Lindénet al.


Varieng - Research Unit for the Study of Variation, Contacts and Change in English

Big Data, Rich Data, Uncharted Data19–22 October 2015Helsinki, Finland

Terttu Nevalainen

Irma TaavitsainenTanja Säilyhttp://www.helsinki.fi/varieng/

http://www.helsinki.fi/varieng/people/varieng_saily.html

et al.


Multilinguallanguage technology

Jörg Tiedemann

Mathias Creutz et al.


Text mining historical newspapers

Mikko Tolonen

Kimmo Kettunen


Citizen MindscapesAnalysis of large social media corporain order to increase understanding of

social and societal phenomena


Educational efforts:e.g. Digital Humanities Hackathon


In many such research efforts andeducational activities, FIN-CLARINserves as an essential resourceand infrastructure.


In many such research efforts andeducational activities, FIN-CLARINserves as an essential resourceand infrastructure.

Let's celebrate andhave a moment

of applause

http://375humanistia.helsinki.fi/en/humanists/kimmo-koskenniemi


Complexity associated withdifferent areas of science

Biological phenomena

Physical phenomena

Cultural phenomena


Importance ofhumanities and social sciences

● As surprising it may at first sound, one can claim that humanities and social sciences are the most important ones

● These disciplines deal with topics like language and communication, social condition, historical developments, economy, etc.

● Due to the complexity, research in these areas is challenging; generalizations commonplacein physics are rarely possible


Understandingthe phenomena

Theory andknowledgeformation

Qualitative Quantitative

Open data:corpora

Openmethods

Computationalresources


Lars Borin

Linguistics hasbeen the first

e-science


Challenges:

“Language is BIG”

“Human INTERPRETATION isinherently involved”

Importance of language:

”Language is involved in mostrelevant human activities”


Example:

Complexity ofFinnish at thelevel of wordforms

Kimmo Koskenniemi (2013):Johdatus kieliteknologiaan,sen merkitykseen ja sovelluksiin(Introduction to language technology, its significance andapplications)

https://helda.helsinki.fi/bitstream/handle/10138/38503/kt-johd.pdf?sequence=1


> 6000 languages,many more dialects Billions of people

blogs.state.gov

en.wikipedia.org

A large number ofdifferent cultures

en.wikipedia.org A vast number of ways to relatelanguage, concepts andthe world to each other

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&docid=fpGjDAgwZeixRM&tbnid=HZkrscZ261waAM:&ved=0CAQQjB0&url=http%3A%2F%2Fblogs.state.gov%2Findex.php%2Fsite%2Fentry%2Fworld_youth_conference_2010&ei=vW9QUeaXGsSstAa9toGAAQ&psig=AFQjCNEVcs0UjcwUK4P2YwfwF_PJ0QJlug&ust=1364312360901232

Simulating processes of language emergence and communication 19


Language as a system

● Considering natural language as a signal and dynamic system at cognitive and social levels (also in its written form) rather than a symbolic and logical system

● Importance of embodiment (cf. e.g. Harnad) and embeddedness (cf. e.g. Edelman)

● Learning and pattern recognition processes are essential (as opposed to the theories presented e.g. by Chomsky, Fodor, Pinker); much of the learning is bound to be unsupervised


Complexity of languageregarding different areas and levels

Structure:morphology and syntax

Meaning: semantics and pragmatics


Complexity of languageregarding different areas and levels

Structure:morphology and syntax

Meaning: semantics and pragmatics

What are the nature,granularity, type,

metadata involved, etc.for different researchpurposes in different

areas of linguistics andother areas of humanities

and social sciences?


Need toharmonize,build sharedterminologies,theories,frameworks, etc.

Need to modelcontextuality,

ambiguity, vagueness,history-dependence,

change, ambiguity,etc.


Need toharmonize,build sharedterminologies,theories,frameworks, etc.

Need to modelcontextuality,

ambiguity, vagueness,history-dependence,

change, ambiguity,etc.

The same medium, language, isthe object of study as well as the

basis for theory formation,representing the ideas and resources, etc.


Philosophy of scienceis essential to

understand whatis going on...

Data-driveninductive mode

Hypothesisdriven,

deductive mode


An old research example:

Data-driven emergenceof implicit word

categories that match withhuman syntactic

and semantic intuitions


Classical example: Learning meaning from context:

Maps of words in Grimm fairy tales

Honkela, Pulkki & Kohonen 1995


Research example:

Multimodallygroundedmodels

of meaning


Labeling movements: Associatinghigh-dim. kinesthetic time series

with linguistic labels

Förger & Honkela 2014


RUNNING

WALKING

LIMPING

JOGGING

Förger & Honkela 2014


Research example:

Tensor-based analysis ofsubjective aspect

of interpreting linguisticexpressions


GICA: Grounded IntersubjectiveConcept Analysis

Honkela et al. 2012


Analysis of the word 'health'

Honkela et al. 2012


Ideas for building corpora

● Espansion of the contextual framework● Enriching metadata● Increasing multimodal data sources

that associate linguistic data with othermodalities

● Involving large number of peoplein labeling data to model variation

● Collecting data in real world contexts