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2008

Using automatically labelled examples to classify rhetorical relations: an assessment

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Using automatically labelled examples to classify rhetorical relations: an assessment
Being able to identify which rhetorical relations (e.g., contrast or explanation) hold between spans of text is important for many natural language processing applications. Using machine learning to obtain a classifier which can distinguish between different relations typically depends on the availability of manually labelled training data, which is very time-consuming to create. However, rhetorical relations are sometimes lexically marked, i.e., signalled by discourse markers (e.g., because, but, consequently etc.), and it has been suggested (Marcu and Echihabi, 2002) that the presence of these cues in some examples can be exploited to label them automatically with the corresponding relation. The discourse markers are then removed and the automatically labelled data are used to train a classifier to determine relations even when no discourse marker is present (based on other linguistic cues such as word co-occurrences). In this paper, we investigate empirically how feasible this appr...
Caroline Sporleder, Alex Lascarides
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2008
Where NLE
Authors Caroline Sporleder, Alex Lascarides
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