Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
Limited attention and discourse structure
Computational Linguistics
An empirical approach to VP ellipsis
Computational Linguistics
ANLC '92 Proceedings of the third conference on Applied natural language processing
The effect of establishing coherence in ellipsis and anaphora resolution
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Learning trees and rules with set-valued features
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Squibs and discussions: human variation and lexical choice
Computational Linguistics - Summarization
Acquiring correct knowledge for natural language generation
Journal of Artificial Intelligence Research
Individual and domain adaptation in sentence planning for dialogue
Journal of Artificial Intelligence Research
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We present conditions under which verb phrases are elided based on a corpus of positive and negative examples. Factor that affect verb phrase ellipsis include: the distance between antecedent and ellipsis site, the syntactic relation between antecedent and ellipsis site, and the presence or absence of adjuncts. Building on these results, we examine where in the generation architecture a trainable algorithm for VP ellipsis should be located. We show that the best performance is achieved when the trainable module is located after the realizer and has access to surface-oriented features (error rate of 7.5%).