Abstract
Discourse relation parsing is an important task with the goal of understanding text beyond the sentence boundaries. With the availability of annotated corpora (Penn Discourse Treebank) statistical discourse parsers were developed. In the literature it was shown that the discourse parsing subtasks of discourse connective detection and relation sense classification do not generalize well across domains. The biomedical domain is of particular interest due to the availability of Biomedical Discourse Relation Bank (BioDRB). In this paper we present cross-domain evaluation of PDTB trained discourse relation parser and evaluate feature-level domain adaptation techniques on the argument span extraction subtask. We demonstrate that the subtask generalizes well across domains.
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