Semantic differentiation of nominal pluralization is grammaticalized in many
languages. For example, plural markers may only be relevant for human nouns.
English does not appear to make such distinctions. Using distributional
semantics, we show that English nominal pluralization exhibits semantic
clusters. For instance, pluralization of fruit words is more similar to one
another and less similar to pluralization of other semantic classes. Therefore,
reduction of the meaning shift in plural formation to the addition of an
abstract plural meaning is too simplistic. A semantically informed method,
called CosClassAvg, is introduced that outperforms pluralization methods in
distributional semantics which assume plural formation amounts to the addition
of a fixed plural vector. In comparison with our approach, a method from
compositional distributional semantics, called FRACSS, predicted plural vectors
that were more similar to the corpus-extracted plural vectors in terms of
direction but not vector length. A modeling study reveals that the observed
difference between the two predicted semantic spaces by CosClassAvg and FRACSS
carries over to how well a computational model of the listener can understand
previously unencountered plural forms. Mappings from word forms, represented
with triphone vectors, to predicted semantic vectors are more productive when
CosClassAvg-generated semantic vectors are employed as gold standard vectors
instead of FRACSS-generated vectors.

使用分布语义学，本文研究了英语名词复数形式的意义聚类，介绍了一种计算方法叫做 CosClassAvg，通过实验比较它与另一种方法 FRACSS 的差异，并验证了 CosClassAvg 方法在语义向量映射中的优越性