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Assessing interpretable, attribute-related meaning representations for adjective-noun phrases in a similarity prediction task
Matthias Hartung and Anette Frank
In: GEometrical Models of Natural Language Semantics (GEMS-2011), Edinburgh, UK(2011).
AbstractWe present a distributional vector space model
that incorporates Latent Dirichlet Allocation
in order to capture the semantic relation holding between adjectives and nouns along interpretable dimensions of meaning: The meaning
of adjective-noun phrases is characterized in
terms of ontological attributes that are prominent in their compositional semantics. The
model is evaluated in a similarity prediction
task based on paired adjective-noun phrases
from the Mitchell and Lapata (2010) benchmark data. Comparing our model against a
high-dimensional latent word space, we observe qualitative differences that shed light
on different aspects of similarity conveyed
by both models and suggest integrating their
complementary strengths. [Edit]
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