TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Wiegand, Michael
A1  - Chikobava, Margarita
A1  - Ruppenhofer, Josef
T1  - A Supervised learning approach for the extraction of opinion sources and targets from German text
T2  - Preliminary proceedings of the 15th Conference on Natural Language Processing (KONVENS 2019), October 9 – 11, 2019 at Friedrich-Alexander-Universität Erlangen-Nürnberg
N2  - 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.
KW  - Deutsch
KW  - Semantische Analyse
KW  - Propositionale Einstellung
KW  - Automatische Sprachanalyse
Y1  - 2019
U6  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-93218
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-93218
UR  - https://corpora.linguistik.uni-erlangen.de/data/konvens/proceedings/papers/KONVENS2019_paper_6.pdf
SP  - 10
EP  - 19
PB  - German Society for Computational Linguistics & Language Technology und Friedrich-Alexander-Universität Erlangen-Nürnberg
CY  - München [u.a.]
ER  -