期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2012
卷号：2012
出版社：ACL Anthology
摘要：This paper studies the problem of sentencelevel
semantic coherence by answering SATstyle
sentence completion questions. These
questions test the ability of algorithms to distinguish
sense from nonsense based on a variety
of sentence-level phenomena. We tackle
the problem with two approaches: methods
that use local lexical information, such as the
n-grams of a classical language model; and
methods that evaluate global coherence, such
as latent semantic analysis. We evaluate these
methods on a suite of practice SAT questions,
and on a recently released sentence completion
task based on data taken from five Conan
Doyle novels. We find that by fusing local
and global information, we can exceed 50%
on this task (chance baseline is 20%), and we
suggest some avenues for further research.
