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.
Cross-lingual Annotation Projection in Legal Texts / Galassi A.; Drazewski K.; Lippi M.; Torroni P.. - ELETTRONICO. - (2020), pp. 915-926. (Intervento presentato al convegno 28th International Conference on Computational Linguistics, COLING 2020 tenutosi a esp nel 2020).
Cross-lingual Annotation Projection in Legal Texts
Lippi M.;
2020
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.
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
