What does distributional semantic model (D.S.M.) mean in natural language processing?

What does distributional semantic model (D.S.M.) mean in natural language processing?

en.wikipedia.org/wiki/Distributional_semantics

Distributional semantics is a research area that develops and studies theories and methods for quantifying and categorizing semantic similarities between linguistic items based on their distributional properties in large samples of language data. The basic idea of distributional semantics can be summed up in the so-called Distributional hypothesis: linguistic items with similar distributions have similar meanings.

In the context of dialog systems, distributional semantics is related to Probabilistic logic, and probabilistic dialog systems or engines, generally based on n-grams, skip-grams, etc. Real linguists tend to pooh-pooh probabilistic techniques. However, despite perhaps not being suited to mission critical applications, I believe probabilistic dialog systems are perfectly adequate for many, if not most, day to day applications in robotics and Internet of Things.