UTFPR at SemEval-2019 Task 6: Relying on Compositionality to Find Offense

Gustavo Henrique Paetzold

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Abstract
We present the UTFPR system for the OffensEval shared task of SemEval 2019: A character-to-word-to-sentence compositional RNN model trained exclusively over the training data provided by the organizers. We find that, although not very competitive for the task at hand, it offers a robust solution to the orthographic irregularity inherent to tweets.
Anthology ID:
S19-2140
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Editors:
Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
801–805
Language:
URL:
https://aclanthology.org/S19-2140
DOI:
10.18653/v1/S19-2140
Bibkey:
Cite (ACL):
Gustavo Henrique Paetzold. 2019. UTFPR at SemEval-2019 Task 6: Relying on Compositionality to Find Offense. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 801–805, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
UTFPR at SemEval-2019 Task 6: Relying on Compositionality to Find Offense (Paetzold, SemEval 2019)
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PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/S19-2140.pdf