Year: 2013
Type: conference-paper
Abstract: We present a classification model that predicts the presence or omission of a lexical connective between two clauses, based upon linguistic features of the clauses and the type of discourse relation holding between them.The model is trained on a set of high frequency relations extracted from the Penn Discourse Treebank and achieves an accuracy of 86.6%.Analysis of the results reveals that the most informative features relate to the discourse dependencies between sequences of coherence relations in the text.We also present results of an experiment that provides insight into the nature and difficulty of the task.
DOI: 10.18653/v1/d13-1094
Authors: Gary Patterson, Andrew Kehler
Institution: University of California San Diego
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2250265609