End-to-End Argument Mining over Varying Rhetorical Structures
Elena Chistova
Rhetorical Structure Theory implies no single discourse interpretation of a
text, and the limitations of RST parsers further exacerbate inconsistent
parsing of similar structures. Therefore, it is important to take into account
that the same argumentative structure can be found in semantically similar
texts with varying rhetorical structures. In this work, the differences between
paraphrases within the same argument scheme are evaluated from a rhetorical
perspective. The study proposes a deep dependency parsing model to assess the
connection between rhetorical and argument structures. The model utilizes
rhetorical relations; RST structures of paraphrases serve as training data
augmentations. The method allows for end-to-end argumentation analysis using a
rhetorical tree instead of a word sequence. It is evaluated on the bilingual
Microtexts corpus, and the first results on fully-fledged argument parsing for
the Russian version of the corpus are reported. The results suggest that
argument mining can benefit from multiple variants of discourse structure.