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Semantic Role Labeling for Sentiment Inference: A Case Study

Klenner, Manfred; Göhring, Anne (2022). Semantic Role Labeling for Sentiment Inference: A Case Study. In: Proceedings of the 18th Conference on Natural Language Processing (KONVENS 2022), Potsdam, 12 September 2022 - 15 September 2022. KONVENS 2022 Organizers, 144-149.

Abstract

In this paper, we evaluate in a case study whether semantic role labelling (SRL) can be reliably used for verb-based sentiment inference (SI). SI strives to identify polar relations (against, in-favour-of) between discourse entities. We took 300 sentences with 10 different verbs that show verb alternations or are ambiguous in order to find out if current SRL systems actually can assign the correct semantic roles and find the correct underlying predicates. Since in SI each verb reading comes with a particular polar profile, SRL is useful only if its analyses are consistent and reliable. We found that this is not (yet) given for German.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Event End Date:15 September 2022
Deposited On:14 Sep 2022 13:15
Last Modified:31 Dec 2022 08:14
Publisher:KONVENS 2022 Organizers
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Official URL:https://aclanthology.org/2022.konvens-1.17.pdf
Related URLs:https://aclanthology.org/2022.konvens-1.17
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  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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