glam/frontend/public/schemas/20251121/linkml/modules/classes/AutoGeneration.yaml
kempersc f9f3cc8e74 fix: resolve YAML import indentation and add missing slot descriptions
Schema Improvements:
- Fix YAML import indentation across 800+ class files (sed: '^- ../' → '  - ../')
- Add descriptions to 26 inline slots missing them (lint warnings)
- Fix malformed imports in BirthPlace.yaml and CustodianObservation.yaml

Validation Results:
- linkml-lint: 4 warnings (intentional SCREAMING_CASE tier names)
- gen-owl: SUCCESS (164,069 lines generated)
- gen-json-schema: SUCCESS (9.4MB generated)

Files affected: 1,034 files, +23,908 -15,200 lines
2026-01-16 00:09:28 +01:00

87 lines
3.1 KiB
YAML

id: https://nde.nl/ontology/hc/class/AutoGeneration
name: auto_generation_class
title: AutoGeneration Class
imports:
- linkml:types
- ../slots/has_or_had_label
- ../slots/has_or_had_description
- ../slots/has_or_had_description
- ../slots/has_or_had_label
- ../slots/has_or_had_description
- ../slots/has_or_had_label
prefixes:
linkml: https://w3id.org/linkml/
hc: https://nde.nl/ontology/hc/
schema: http://schema.org/
prov: http://www.w3.org/ns/prov#
dcterms: http://purl.org/dc/terms/
default_prefix: hc
classes:
AutoGeneration:
class_uri: prov:Activity
description: >-
Represents automatic generation or creation of content by a system or algorithm.
**DEFINITION**:
AutoGeneration models the automatic creation of content such as subtitles,
chapters, transcripts, or metadata by AI/ML systems, platform algorithms,
or automated processes. This replaces simple boolean flags like `auto_generated`
with a structured class that can capture the generation method and provenance.
**ONTOLOGY ALIGNMENT**:
- PROV-O: `prov:Activity` - an activity that generates entities
- PROV-O: `prov:wasGeneratedBy` - links to generating activity
- Schema.org: `schema:CreateAction` - creation action
**GENERATION METHODS**:
- ASR (Automatic Speech Recognition): Speech-to-text for subtitles
- Scene Detection: AI-based video chapter generation
- NLP: Natural language processing for metadata extraction
- OCR: Optical character recognition for text extraction
**USE CASES**:
1. **Auto-Subtitles**: YouTube auto-generated captions
2. **Auto-Chapters**: AI-detected video chapters
3. **Auto-Transcripts**: ASR-generated transcripts
4. **Auto-Metadata**: ML-extracted metadata
exact_mappings:
- prov:Activity
close_mappings:
- schema:CreateAction
related_mappings:
- prov:wasGeneratedBy
slots:
- has_or_had_label
- has_or_had_description
slot_usage:
has_or_had_label:
range: string
examples:
- value: "YouTube Auto-Caption"
description: Platform auto-generated captions
- value: "ASR Transcription"
description: Automatic speech recognition
has_or_had_description:
range: string
examples:
- value: "Automatically generated by YouTube's speech recognition system"
description: Platform-provided auto-generation
- value: "Generated using Whisper ASR model"
description: Specific ASR model used
comments:
- Generic auto-generation class replacing domain-specific boolean flags
- Captures generation method and provenance
- Aligns with PROV-O Activity for provenance tracking
see_also:
- https://www.w3.org/TR/prov-o/#Activity
- https://schema.org/CreateAction
examples:
- value:
has_or_had_label: "YouTube Auto-Caption"
has_or_had_description: "Automatically generated by YouTube's speech recognition"
description: YouTube auto-generated subtitles