Experimental Support for a Categorical Compositional Distributional Model of Meaning

Understand

Modelling compositional meaning for sentences using empirical distributional methods has been a challenge for computational linguists.

• We implement the abstract categorical model of Coecke et al.
• (arXiv:1003.4394v1 [cs.CL]) using data from the BNC and evaluate it.
• The implementation is based on unsupervised learning of matrices for relational words and applying them to the vectors of their arguments.