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feat: expand individual entity type detection for diverse simulation scenarios#32

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back2zion wants to merge 1 commit intonikmcfly:mainfrom
back2zion:feat/expand-individual-entity-types
Open

feat: expand individual entity type detection for diverse simulation scenarios#32
back2zion wants to merge 1 commit intonikmcfly:mainfrom
back2zion:feat/expand-individual-entity-types

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Summary

  • The ontology generator creates domain-specific entity types (e.g. DataArchitect, AIConsultant, MachineLearningEngineer) that are not in INDIVIDUAL_ENTITY_TYPES
  • These entities fall through to the group/institutional path, resulting in hardcoded age (30) and uniform MBTI for all agents
  • This makes simulations with professional/expert personas produce identical demographic profiles

Changes

  • Expanded INDIVIDUAL_ENTITY_TYPES with common professional roles (consultant, engineer, architect, researcher, etc.)
  • Added fallback logic: unknown entity types now default to individual instead of group, since GROUP_ENTITY_TYPES is a well-defined, shorter list

Before

All domain-specific entities → group persona → age: 30, MBTI: ISTJ

After

Domain-specific entities → individual persona → diverse age, MBTI, and personality traits generated by LLM

Test plan

  • Verified entities like DataArchitect, MachineLearningEngineer are now classified as individual
  • Confirmed LLM generates diverse age/MBTI profiles for professional personas

The ontology generator creates domain-specific entity types like
DataArchitect, AIConsultant, MachineLearningEngineer etc. These
were not in the INDIVIDUAL_ENTITY_TYPES list, causing all such
entities to be classified as group/institutional types with
hardcoded age (30) and uniform MBTI profiles.

Changes:
- Added common professional roles to INDIVIDUAL_ENTITY_TYPES
- Added fallback: unknown types default to individual instead of
  group, since GROUP_ENTITY_TYPES is a shorter, well-defined list
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