期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2009
卷号：2009
出版社：ACL Anthology
摘要：We describe a methodology for learning a
disambiguation model for deep pragmatic
interpretations in the context of situated
task-oriented dialogue. The system accumulates
training examples for ambiguity
resolution by tracking the fates of alternative
interpretations across dialogue, including
subsequent clarificatory episodes
initiated by the system itself. We illustrate
with a case study building maximum
entropy models over abductive interpretations
in a referential communication
task. The resulting model correctly resolves
81% of ambiguities left unresolved
by an initial handcrafted baseline. A key
innovation is that our method draws exclusively
on a system’s own skills and experience
and requires no human annotation.
