Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!
Steffen Eger, Johannes Daxenberger, Christian Stab, Iryna Gurevych
Abstract
Argumentation mining (AM) requires the identification of complex discourse structures and has lately been applied with success monolingually. In this work, we show that the existing resources are, however, not adequate for assessing cross-lingual AM, due to their heterogeneity or lack of complexity. We therefore create suitable parallel corpora by (human and machine) translating a popular AM dataset consisting of persuasive student essays into German, French, Spanish, and Chinese. We then compare (i) annotation projection and (ii) bilingual word embeddings based direct transfer strategies for cross-lingual AM, finding that the former performs considerably better and almost eliminates the loss from cross-lingual transfer. Moreover, we find that annotation projection works equally well when using either costly human or cheap machine translations. Our code and data are available at http://github.com/UKPLab/coling2018-xling_argument_mining.- Anthology ID:
- C18-1071
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Emily M. Bender, Leon Derczynski, Pierre Isabelle
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 831–844
- Language:
- URL:
- https://aclanthology.org/C18-1071
- DOI:
- Cite (ACL):
- Steffen Eger, Johannes Daxenberger, Christian Stab, and Iryna Gurevych. 2018. Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!. In Proceedings of the 27th International Conference on Computational Linguistics, pages 831–844, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need! (Eger et al., COLING 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/C18-1071.pdf
- Code
- UKPLab/coling2018-xling_argument_mining