Despite the incremental nature of Dynamic Syntax (DS), the semantic
grounding of it remains that of predicate logic, itself grounded in set theory,
so is poorly suited to expressing the rampantly context-relative nature
of word meaning, and related phenomena such as incremental judgements
of similarity needed for the modelling of disambiguation. Here, we show
how DS can be assigned a compositional distributional semantics which
enables such judgements and makes it possible to incrementally disambiguate
language constructs using vector space semantics. Building on a
proposal in our previous work, we implement and evaluate our model on
real data, showing that it outperforms a commonly used additive baseline.
In conclusion, we argue that these results set the ground for an account
of the non-determinism of lexical content, in which the nature of word
meaning is its dependence on surrounding context for its construal
