CNTS: memory-based learning of generating repeated references
Iris Hendrickx, Walter Daelemans, Kim Luyckx, Roser Morante and Vincent Van Asch
In: 5th International Natural Language Generation Conference, 12-14 Jun 2008, Ohio, USA.
In this paper we describe our machine learning
approach to the generation of referring expressions.
As our algorithm we use memory-based
learning. Our results show that in case of predicting
the TYPE of the expression, having one
general classifier gives the best results. On the
contrary, when predicting the full set of properties
of an expression, a combined set of specialized
classifiers for each subdomain gives
the best performance.