Assessing Interpretable, Attribute-related Meaning Representations for Adjective-Noun Phrases in a Similarity Prediction Task
Matthias Härtung, Anette Frank · PUB – Publications at Bielefeld University (Bielefeld University) · 2011
We 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.