granularitystems
Granularitystems are a theoretical class of morphemes used in linguistic annotation to encode granularity information about referents or events. A granularitystem marks the level of detail, or scale, at which a word’s reference is intended to be interpreted, such as fine-grained (micro) or coarse-grained (macro). They are proposed as metadata that can be attached to base words without changing core lexical meaning, but with implications for interpretation and processing in downstream tasks.
Origin and usage have been discussed mainly in corpus linguistics and natural language processing environments that
Form and interaction: granularitystems can attach to noun or verb bases as prefixes, suffixes, or clausal particles,
Examples: in an experimental annotation system, a granularitystem micro- attached to “cell” could signal a micro-level
Applications: granularitystems are used to support granularity-aware search, semantic parsing, corpus annotation, and knowledge graph construction,