Encontexts
Encontexts are modular, hierarchical sets of contextual constraints that accompany data, actions, or queries to guide interpretation and decision making in AI systems. The approach treats context as a structured, composable bundle rather than a single static field, enabling dynamic reconfiguration as tasks, users, and environments change.
Typical encontexts encompass multiple components: temporal context (when the data was produced and relevant timescales); spatial
Encontexts are often stored in a context store or represented as a graph, allowing systems to compose,
Applications include chatbots that tailor responses to user goals, recommendation engines that respect situational constraints, and
See also: context-aware computing, provenance, knowledge graphs, discourse analysis.