Introducing Structure into Neural Network-Based Semantic Models

In this talk I will describe two attempts at introducing syntactic structure into semantic models using neural network architectures. The first study focuses on a particular grammatical construction, namely relative clauses, and centers around the design of a new dataset for testing compositional distributional models. The dataset is called RELPRON, and consists of pairs of terms and properties, such as