Semi-automatic Theme-Rheme Identification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F13%3A00070352" target="_blank" >RIV/00216224:14330/13:00070352 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Semi-automatic Theme-Rheme Identification
Original language description
In this paper we start from the theory of the Functional Sentence Perspective developed primarily by Firbas [1], Svoboda [2] and also Sgall, Hajicová [3] and make an attempt to formulate a procedure allowing to semi-automatically recognize which sentenceconstituents carry information that is contextually dependent and thus known to an adressee (theme), constituents containing new information (rheme), and also constituents bearing non-thematic and non-rhematic information (transition). Having themes andrhemes recognized as successfully as possible we also hope to investigate thematic progression (thematic line) in texts in the future. The core of the procedure and its experimental implementation for Czech (using the bushbank corpus CBB.Blog [4] as a data source) are described in the paper. Since the task is really complicated we only offer basic evaluation, which, in our view, shows that the task is feasible.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/LM2010013" target="_blank" >LM2010013: LINDAT-CLARIN: Institute for analysis, processing and distribution of linguistic data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Seventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2013
ISBN
9788026305200
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
39-48
Publisher name
Tribun EU
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2013
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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