Abstract
We present TARGER, an open source neural argument mining framework for tagging arguments in free input texts and for keyword-based retrieval of arguments from an argument-tagged web-scale corpus. The currently available models are pre-trained on three recent argument mining datasets and enable the use of neural argument mining without any reproducibility effort on the user's side. The open source code ensures portability to other domains and use cases, such as an application to search engine ranking that we also describe shortly.
Cite
CITATION STYLE
Chernodub, A., Oliynyk, O., Heidenreich, P., Bondarenko, A., Hagen, M., Biemann, C., & Panchenko, A. (2019). TARGER: Neural argument mining at your fingertips. In ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations. Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/p19-3031
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