Konferenzbeitrag
A Supervised learning approach for the extraction of opinion sources and targets from German text
We present the first systematic supervised learning approach for the extraction of opinion sources and targets on German language data. A wide choice of different features is presented, particularly syntactic features and generalization features. We point out specific differences between opinion sources and targets. Moreover, we explain why implicit sources can be extracted even with fairly generic features. In order to ensure comparability our classifier is trained and tested on the dataset of the STEPS shared task.
- Language
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Englisch
- Subject
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Deutsch
Semantische Analyse
Propositionale Einstellung
Automatische Sprachanalyse
Sprache
- Event
-
Geistige Schöpfung
- (who)
-
Wiegand, Michael
Chikobava, Margarita
Ruppenhofer, Josef
- Event
-
Veröffentlichung
- (who)
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München [u.a.] : German Society for Computational Linguistics & Language Technology und Friedrich-Alexander-Universität Erlangen-Nürnberg
- (when)
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2019-10-15
- URN
-
urn:nbn:de:bsz:mh39-93218
- Last update
-
06.03.2025, 9:00 AM CET
Data provider
This object is provided by:
Leibniz-Institut für Deutsche Sprache - Bibliothek. If you have any questions about the object, please contact the data provider.
Leibniz-Institut für Deutsche Sprache - Bibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Konferenzbeitrag
Associated
- Wiegand, Michael
- Chikobava, Margarita
- Ruppenhofer, Josef
- München [u.a.] : German Society for Computational Linguistics & Language Technology und Friedrich-Alexander-Universität Erlangen-Nürnberg
Time of origin
- 2019-10-15
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Disambiguation of verbal shifters
Opinion Holder and Target Extraction based on the Induction of Verbal Categories
Opinion Holder and Target Extraction on Opinion Compounds – A Linguistic Approach
Opinion Holder and Target Extraction for Verb-based Opinion Predicates – The Problem is Not Solved
Exploiting emojis for abusive language detection
Enhancing a Lexicon of Polarity Shifters through the Supervised Classification of Shifting Directions
Separating Actor-View from Speaker-View Opinion Expressions using Linguistic Features
A descriptive analysis of a German corpus annotated with opinion sources and targets
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Overview of the IGGSA 2016 Shared Task on Source and Target Extraction from Political Speeches
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