Abstract
Discourse relation identification has been an
active area of research for many years, and the
challenge of identifying implicit relations remains largely an unsolved task, especially in
the context of an open-domain dialogue system. Previous work primarily relies on a corpora of formal text which is inherently nondialogic, i.e., news and journals. This data
however is not suitable to handle the nuances
of informal dialogue nor is it capable of navigating the plethora of valid topics present
in open-domain dialogue. In this paper, we
designed a novel discourse relation identifi-
cation pipeline specifically tuned for opendomain dialogue systems. We firstly propose
a method to automatically extract the implicit
discourse relation argument pairs and labels
from a dataset of dialogic turns, resulting in
a novel corpus of discourse relation pairs; the
first of its kind to attempt to identify the discourse relations connecting the dialogic turns
in open-domain discourse. Moreover, we have
taken the first steps to leverage the dialogue
features unique to our task to further improve
the identification of such relations by performing feature ablation and incorporating dialogue features to enhance the state-of-the-art
model