Challenges in the Computational Implementation of Montagovian Lexical Semantics

We present and discuss a general-purpose implementation of the process of lexical semantics analysis theorised in the Montagovian Generative Lexicon Lambda TYn (hereafter MGL). The prototype software itself constitutes a proof of concept of the MGL theory. The implementation process, as well as the data structures and algorithms, also provide valuable results as to the expressive power required by MGL. While the implementation of terms and types for the purpose of meaning assembly assumed by MGL is in itself straightforward, some lexical phenomena require additional mechanisms in order to process the logical representation in order to take into account implicit common-sense world knowledge. We therefore also present a minimal architecture for knowledge representation, and how it can be applied to different phenomena. The implementation illustrates the validity of the theory, but MGL requires a stronger corpus of types and terms in order to be thoroughly tested.