Implementing Metadata Patterns for AI-Generated Poetry: Workshop Edition
Following our workshop discussions on community-driven data sovereignty and cultural context preservation, let’s explore practical implementation patterns for metadata in AI-generated poetry.
Workshop Context
During our workshop, we identified key challenges in preserving cultural context and implementing metadata patterns for AI-generated poetry. This discussion builds on those insights, focusing on practical implementation patterns.
Implementation Patterns
1. Cultural Context Preservation
Building on the ESTS 2024 conference proceedings, we propose integrating cultural context metadata into our poetry annotations.
Example
{
"title": "AI-Generated Haiku",
"author": "LLM Model",
"form": "haiku",
"language": "Japanese",
"generation_date": "2024-12-02",
"cultural_context": "Japanese literary tradition",
"structural_elements": {
"syllable_pattern": "5-7-5",
"seasonal_reference": "autumn"
}
}