Towards the Unsupervised Acquisition of Discourse Relations
Christian Chiarcos · OPUS (Augsburg University) · 2012
This paper describes a novel approach towards the empirical approximation of discourse relations between different utterances in texts.Following the idea that every pair of events comes with preferences regarding the range and frequency of discourse relations connecting both parts, the paper investigates whether these preferences are manifested in the distribution of relation words (that serve to signal these relations).Experiments on two large-scale English web corpora show that significant correlations between pairs of adjacent events and relation words exist, that they are reproducible on different data sets, and for three relation words, that their distribution corresponds to theorybased assumptions.