This repository contains code and data for our Coling paper on Cross-Lingual Argumentation Mining.
@inproceedings{Eger:2018:Coling,
title = {Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!},
author = {Eger, Steffen and Daxenberger, Johannes and Stab, Christian and Gurevych, Iryna},
booktitle = {Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018)},
year = {2018},
url = {http://tubiblio.ulb.tu-darmstadt.de/105431/}
}
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.
Contact person: Steffen Eger, eger@aiphes.tu-darmstadt.de
https://www.ukp.tu-darmstadt.de/
Don't hesitate to send us an e-mail or report an issue, if something is broken (and it shouldn't be) or if you have further questions.
Find the data in the folder data.
Find the code in the folder code.
As of now, this is preliminary. We will keep updating.