A Compositional Distributional Inclusion Hypothesis

Abstract

The distributional inclusion hypothesis provides a pragmatic way of evaluating entailment between word vectors as represented in a distributional model of meaning. In this paper, we extend this hypothesis to the realm of com- positional distributional semantics, where meanings of phrases and sentences are computed by composing their word vectors. We present a theoretical analysis for how feature inclusion is interpreted under each composition operator, and propose a measure for evaluating entailment at the phrase/sentence level. We perform ex- periments on four entailment datasets, showing that intersective composition in conjunction with our proposed measure achieves the highest performance.