Automatic Assignment of Semantic Frames in Disaster Response Team Communication Dialogues

Natalia Skachkova, Ivana Kruijff-Korbayova


Abstract
We investigate frame semantics as a meaning representation framework for team communication in a disaster response scenario. We focus on the automatic frame assignment and retrain PAFIBERT, which is one of the state-of-the-art frame classifiers, on English and German disaster response team communication data, obtaining accuracy around 90%. We examine the performance of both models and discuss their adjustments, such as sampling of additional training instances from an unrelated domain and adding extra lexical and discourse features to input token representations. We show that sampling has some positive effect on the German frame classifier, discuss an unexpected impact of extra features on the models’ behaviour and perform a careful error analysis.
Anthology ID:
2021.iwcs-1.10
Volume:
Proceedings of the 14th International Conference on Computational Semantics (IWCS)
Month:
June
Year:
2021
Address:
Groningen, The Netherlands (online)
Venue:
IWCS
SIG:
SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
93–109
Language:
URL:
https://aclanthology.org/2021.iwcs-1.10
DOI:
Bibkey:
Cite (ACL):
Natalia Skachkova and Ivana Kruijff-Korbayova. 2021. Automatic Assignment of Semantic Frames in Disaster Response Team Communication Dialogues. In Proceedings of the 14th International Conference on Computational Semantics (IWCS), pages 93–109, Groningen, The Netherlands (online). Association for Computational Linguistics.
Cite (Informal):
Automatic Assignment of Semantic Frames in Disaster Response Team Communication Dialogues (Skachkova & Kruijff-Korbayova, IWCS 2021)
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PDF:
https://aclanthology.org/2021.iwcs-1.10.pdf
Attachment:
 2021.iwcs-1.10.Attachment.zip
Data
FrameNet