Existing cultural commonsense benchmarks treat nations as monolithic, assuming uniform practices within national boundaries. But does cultural commonsense hold uniformly within a nation, or does it vary at the sub-national level? We introduce **Indica**, the first benchmark designed to test LLMs’ ability to address this question, focusing on India—a nation of 28 states, 8 union territories, and 22 official languages. We collect human-annotated answers from five Indian regions (North, South, East, West, and Central) across 515 questions spanning 8 domains of everyday life, yielding 1,630 region-specific question-answer pairs. Strikingly, only 39.4% of questions elicit agreement across all five regions, demonstrating that cultural commonsense in India is predominantly regional, not national. We evaluate eight state-of-the-art LLMs and find two critical gaps: models achieve only 13.4%–20.9% accuracy on region-specific questions, and they exhibit geographic bias, over-selecting Central and North India as the "default" (selected 30-40% more often than expected) while under-representing East and West. Beyond India, our methodology provides a generalizable framework for evaluating cultural commonsense in any culturally heterogeneous nation, from question design grounded in anthropological taxonomy, to regional data collection, to bias measurement.

The objective of the Semiotic-based Ontology Evaluation Tool (S-OntoEval) is to evaluate and propose improvements to a given ontological model. The evaluation aims at assessing the quality of the ontology by drawing upon semiotic theory, taking several metrics into consideration for assessing the syntactic, semantic, and pragmatic aspects of ontology quality. We consider an ontology to be a semiotic object and we identify three main types of semiotic ontology evaluation levels: the structural level, assessing the ontology syntax and formal semantics; the functional level, assessing the ontology cognitive semantics and; the usability-related level, assessing the ontology pragmatics. The Ontology Evaluation Tool implements metrics for each semiotic ontology level: on the structural level by making use of reasoner such as the RACER System and Pellet to check the logical consistency of our ontological model (TBoxes and ABoxes) and graph-theory measures such as Depth; on the functional level by making use of a task-based evaluation approach which measures the quality of the ontology based on the adequacy of the ontological model for a specific task; and on the usability-profiling level by applying a quantitative analysis of the amount of annotation. Other metrics can be easily integrated and added to the respective evaluation level. In this work, the Ontology Evaluation Tool is used to test and evaluate the SWIntO Ontology of the SmartWeb project.