1516d509cf
- Added `id`, `name`, `title`, and `description` fields to multiple LinkML class YAML files. - Standardized prefixes across all class definitions. - Introduced a new script `fix_linkml_metadata.py` to automate the addition of metadata to class files. - Updated existing class files to ensure compliance with the new metadata structure.
173 lines
6.3 KiB
YAML
173 lines
6.3 KiB
YAML
id: https://nde.nl/ontology/hc/class/ReasoningContent
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name: ReasoningContent
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title: Reasoning Content
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description: LinkML class definition for Reasoning Content
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prefixes:
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linkml: https://w3id.org/linkml/
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schema: http://schema.org/
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skos: http://www.w3.org/2004/02/skos/core#
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rico: https://www.ica.org/standards/RiC/ontology#
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wd: http://www.wikidata.org/entity/
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# ReasoningContent - LLM reasoning content preservation class
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#
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# Created: 2026-01-19
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# Migration: clear_thinking → preserves_or_preserved + ReasoningContent class
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# Per slot_fixes.yaml, Rule 53/56
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#
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# Rule compliance: 0b (structured class), 37 (specificity), 50 (ontology mapping)
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id: https://nde.nl/ontology/hc/class/ReasoningContent
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name: reasoning_content_class
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title: Reasoning Content Class
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prefixes:
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linkml: https://w3id.org/linkml/
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hc: https://nde.nl/ontology/hc/
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schema: http://schema.org/
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prov: http://www.w3.org/ns/prov#
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default_prefix: hc
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imports:
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- linkml:types
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- ../slots/has_or_had_label
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- ../slots/has_or_had_description
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- ../slots/has_or_had_identifier
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classes:
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ReasoningContent:
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class_uri: prov:Entity
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description: |
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LLM reasoning content that is preserved across conversation turns.
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**DEFINITION**:
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ReasoningContent represents the chain-of-thought reasoning that LLMs like
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GLM 4.7 expose through their thinking modes. This class captures the
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reasoning_content that should be preserved when using "Preserved Thinking"
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mode for multi-turn conversations.
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**GLM 4.7 Preserved Thinking** (https://docs.z.ai/guides/capabilities/thinking-mode):
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When `clear_thinking: false` (Preserved Thinking enabled):
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- Reasoning content from previous turns is retained in context
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- Improves model performance and increases cache hit rates
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- Requires returning EXACT, UNMODIFIED reasoning_content back to API
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**Migration from clear_thinking**:
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This class replaces the boolean `clear_thinking` slot with a structured
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representation of what is being preserved:
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| Old Pattern | New Pattern |
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|-------------|-------------|
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| `clear_thinking: false` | `preserves_or_preserved: ReasoningContent` with `is_preserved: true` |
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| `clear_thinking: true` | `preserves_or_preserved: ReasoningContent` with `is_preserved: false` |
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**PROV-O Alignment**:
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- ReasoningContent IS a prov:Entity (the reasoning output)
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- Links to LLMResponse via preserves_or_preserved slot
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- Enables tracking reasoning provenance across turns
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**Use Cases**:
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- Multi-turn agent conversations with preserved context
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- Debugging reasoning chain across API calls
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- Auditing LLM decision-making process
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- Optimizing cache hit rates
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exact_mappings:
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- prov:Entity
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close_mappings:
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- schema:Comment
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- schema:Review
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slots:
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- has_or_had_label
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- has_or_had_description
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- has_or_had_identifier
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attributes:
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is_preserved:
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range: boolean
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required: true
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description: |
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Whether this reasoning content is preserved across turns.
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- **true**: Preserved Thinking enabled (keep reasoning, better cache hits)
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- **false**: Clear previous reasoning (fresh context each turn)
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Maps to the inverse of the old `clear_thinking` boolean:
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- `is_preserved: true` ≡ `clear_thinking: false`
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- `is_preserved: false` ≡ `clear_thinking: true`
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content_text:
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range: string
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required: false
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description: |
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The actual reasoning content text (chain-of-thought).
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Optional - may be omitted if only tracking preservation status.
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examples:
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- value: |
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The user is asking about Dutch heritage institutions. I need to identify:
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1) Institution name: Rijksmuseum
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2) Type: Museum (maps to InstitutionTypeEnum.MUSEUM)
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3) Location: Amsterdam (city in Noord-Holland province)...
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description: GLM 4.7 reasoning trace
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turn_number:
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range: integer
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required: false
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description: |
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The conversation turn number this reasoning came from.
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Useful for tracking reasoning provenance across multi-turn conversations.
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token_count:
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range: integer
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required: false
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description: |
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Number of tokens in the reasoning content.
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Important for context window management.
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slot_usage:
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has_or_had_label:
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description: Human-readable label for this reasoning content.
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examples:
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- value: Turn 3 Reasoning
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description: Reasoning from the third conversation turn
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has_or_had_description:
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description: Description of the reasoning context or purpose.
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examples:
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- value: Chain-of-thought reasoning for heritage institution extraction
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description: Purpose of the preserved reasoning
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has_or_had_identifier:
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description: Unique identifier for this reasoning content block.
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examples:
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- value: reasoning-turn-3-20260119-143000
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description: Timestamped reasoning block ID
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annotations:
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specificity_score: 0.80
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specificity_rationale: Highly specific to LLM API reasoning preservation domain
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custodian_types: '["D"]'
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custodian_types_rationale: Applies to Digital Platform custodians using LLM APIs
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examples:
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- value:
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is_preserved: true
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has_or_had_label: Preserved Reasoning
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content_text: |
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The user is asking about Dutch heritage institutions...
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turn_number: 3
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token_count: 250
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description: Preserved reasoning content from turn 3
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- value:
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is_preserved: false
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has_or_had_label: Cleared Context
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has_or_had_description: Fresh context for new query topic
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description: Cleared reasoning (fresh context)
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comments:
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- Created from slot_fixes.yaml migration (2026-01-19)
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- Replaces boolean clear_thinking with structured reasoning preservation
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- Enables tracking what reasoning is preserved and why
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- PROV-O Entity alignment for provenance tracking
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