  This paper introduces a natural language understanding (NLU) framework for
argumentative dialogue systems in the information-seeking and opinion building
domain. Our approach distinguishes multiple user intents and identifies system
arguments the user refers to in his or her natural language utterances. Our
model is applicable in an argumentative dialogue system that allows the user to
inform him-/herself about and build his/her opinion towards a controversial
topic. In order to evaluate the proposed approach, we collect user utterances
for the interaction with the respective system and labeled with intent and
reference argument in an extensive online study. The data collection includes
multiple topics and two different user types (native speakers from the UK and
non-native speakers from China). The evaluation indicates a clear advantage of
the utilized techniques over baseline approaches, as well as a robustness of
the proposed approach against new topics and different language proficiency as
well as cultural background of the user.
