Paper: Reducing Dimensions of Tensors in Type-Driven Distributional Semantics

ACL ID D14-1111
Title Reducing Dimensions of Tensors in Type-Driven Distributional Semantics
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

Compositional distributional semantics is a subfield of Computational Linguistics which investigates methods for represent- ing the meanings of phrases and sen- tences. In this paper, we explore im- plementations of a framework based on Combinatory Categorial Grammar (CCG), in which words with certain grammatical types have meanings represented by multi- linear maps (i.e. multi-dimensional arrays, or tensors). An obstacle to full implemen- tation of the framework is the size of these tensors. We examine the performance of lower dimensional approximations of tran- sitive verb tensors on a sentence plausi- bility/selectional preference task. We find that the matrices perform as well as, and sometimes even better than, full tensors, allowing a reduction in the number of pa- rameters needed to...