We experiment with two recent contextualized word embedding methods (ELMo and BERT) in the context of open-domain argument search.
Argument mining has become a popular research area in NLP.
Argumentation is arguably one of the central features of scientific language.
Common-sense argumentative reasoning is a challenging task that requires holistic understanding of the argumentation where external knowledge about the world is hypothesized to play a key role.
Argument Mining (AM) is a relatively recent discipline, which concentrates on extracting claims or premises from discourses, and inferring their structures.