A Proof-Theoretic Approach to Scope Ambiguity in Compositional Vector Space Models
This work addresses a specific linguistic modeling challenge for computational semantics, representing an incremental improvement by integrating existing formal methods.
The paper tackles the problem of modeling scope ambiguity in quantified sentences using compositional vector space models, establishing a derivational procedure to obtain vector space representations for both direct and inverse scope readings.
We investigate the extent to which compositional vector space models can be used to account for scope ambiguity in quantified sentences (of the form "Every man loves some woman"). Such sentences containing two quantifiers introduce two readings, a direct scope reading and an inverse scope reading. This ambiguity has been treated in a vector space model using bialgebras by (Hedges and Sadrzadeh, 2016) and (Sadrzadeh, 2016), though without an explanation of the mechanism by which the ambiguity arises. We combine a polarised focussed sequent calculus for the non-associative Lambek calculus NL, as described in (Moortgat and Moot, 2011), with the vector based approach to quantifier scope ambiguity. In particular, we establish a procedure for obtaining a vector space model for quantifier scope ambiguity in a derivational way.