LTL-UDE at SemEval-2019 Task 6: BERT and Two-Vote Classification for Categorizing Offensiveness

Aggarwal, Piush; Horsmann, Tobias; Wojatzki, Michael; Zesch, Torsten

doi:10.18653/v1/S19-2121

Tagungsbeitrag 2019 CC BY 4.0

Veröffentlicht

LTL-UDE at SemEval-2019 Task 6: BERT and Two-Vote Classification for Categorizing Offensiveness

Aggarwal, Piush ; Horsmann, Tobias ; Wojatzki, Michael ; Zesch, Torsten

This paper describes LTL-UDE’s systems for the SemEval 2019 Shared Task 6. We present results for Subtask A and C. In Subtask A, we experiment with an embedding representation of postings and use a Multi-Layer Perceptron and BERT to categorize postings. Our best result reaches the 10th place (out of 103) using BERT. In Subtask C, we applied a two-vote classification approach with minority fallback, which is placed on the 19th rank (out of 65).

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Einordnung

Konferenz:: NAACL HLT 2019, 13th International Workshop on Semantic Evaluation (SemEval 2019), June 6–June 7, 2019 Minneapolis, Minnesota, USA
Datum der Veröffentlichung:: 2019
URN:: urn:nbn:de:hbz:464-20211019-094140-7
DOI:: 10.18653/v1/S19-2121
Sprache:: Englisch
Ressourcentyp:: Text
Kollektion:: E-Publikationen
Sachgruppen der Deutschen Nationalbibliographie:: 004 Informatik
Einrichtung:: Fakultät für Ingenieurwissenschaften, Informatik und Angewandte Kognitionswissenschaft, Informatik, Sprachtechnologie
Abgrenzungspolitik:: Aggarwal, P., Horsmann, T., Wojatzki, M., Zesch, T. (2019): LTL-UDE at SemEval-2019 Task 6: BERT and Two-Vote Classification for Categorizing Offensiveness. In: Proceedings of the 13th International Workshop on Semantic Evaluation (SemEval 2019), pp. 678-682. Association for Computational Linguistics. DOI: https://doi.org/10.18653/v1/S19-2121