Sentence examples for semantic disparity from inspiring English sources
Here we attempt to qualitatively evaluate the ease of semantic disparity image interpretation with a bias towards the clarity and temporal stability of scene foreground objects (e.g. pedestrians/vehicles/street furniture).
Because all FIRE primary care physicians were located in the German speaking part of Switzerland, we restricted all analyses to residents of that area, thus avoiding bias due to different operating customs as well as cultural and semantic disparities.
One major challenge is related to disparity and semantic mismatching between related context elements across ontologies [35],[35].
Overall we see foreground object cohesivity, connectedness and separation across all of the five algorithms that lends itself well to the manual (or automatic) semantic intrepretation of the disparity image in isolation.
Our evaluation, in contrast to the earlier work of [8], considers the semantic interpretation of the resulting disparity map in terms of object cohesivity, connectedness and separation within the environment.
That is, despite the aforementioned disparity of the syntactic encoding order in Chinese, German, and Polish, the semantic encoding order of the two sentential parts may not differ between languages.
The central problem is the great disparities between language and music, in terms of the ways in which each is both syntactic and semantic (Jackendoff 2011).
Is this semantic quibbling?
Semantic infiltration indeed.
