Cross-lingual Annotation Projection in Legal Texts

Andrea Galassi, Kasper Drazewski, Marco Lippi, Paolo Torroni


Abstract
We study annotation projection in text classification problems where source documents are published in multiple languages and may not be an exact translation of one another. In particular, we focus on the detection of unfair clauses in privacy policies and terms of service. We present the first English-German parallel asymmetric corpus for the task at hand. We study and compare several language-agnostic sentence-level projection methods. Our results indicate that a combination of word embeddings and dynamic time warping performs best.
Anthology ID:
2020.coling-main.79
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Editors:
Donia Scott, Nuria Bel, Chengqing Zong
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
915–926
Language:
URL:
https://aclanthology.org/2020.coling-main.79
DOI:
10.18653/v1/2020.coling-main.79
Bibkey:
Cite (ACL):
Andrea Galassi, Kasper Drazewski, Marco Lippi, and Paolo Torroni. 2020. Cross-lingual Annotation Projection in Legal Texts. In Proceedings of the 28th International Conference on Computational Linguistics, pages 915–926, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
Cross-lingual Annotation Projection in Legal Texts (Galassi et al., COLING 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.coling-main.79.pdf