@inproceedings{galassi-etal-2020-cross,
title = "Cross-lingual Annotation Projection in Legal Texts",
author = "Galassi, Andrea and
Drazewski, Kasper and
Lippi, Marco and
Torroni, Paolo",
editor = "Scott, Donia and
Bel, Nuria and
Zong, Chengqing",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2020.coling-main.79/",
doi = "10.18653/v1/2020.coling-main.79",
pages = "915--926",
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."
}
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%0 Conference Proceedings
%T Cross-lingual Annotation Projection in Legal Texts
%A Galassi, Andrea
%A Drazewski, Kasper
%A Lippi, Marco
%A Torroni, Paolo
%Y Scott, Donia
%Y Bel, Nuria
%Y Zong, Chengqing
%S Proceedings of the 28th International Conference on Computational Linguistics
%D 2020
%8 December
%I International Committee on Computational Linguistics
%C Barcelona, Spain (Online)
%F galassi-etal-2020-cross
%X 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.
%R 10.18653/v1/2020.coling-main.79
%U https://aclanthology.org/2020.coling-main.79/
%U https://doi.org/10.18653/v1/2020.coling-main.79
%P 915-926
Markdown (Informal)
[Cross-lingual Annotation Projection in Legal Texts](https://aclanthology.org/2020.coling-main.79/) (Galassi et al., COLING 2020)
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.