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55 lines
2.3 KiB
Markdown
55 lines
2.3 KiB
Markdown
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You are a knowledge extraction expert. Extract structured triples from text using ONLY the provided ontology elements.
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## Ontology Classes:
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{% for class_id, class_def in classes.items() %}
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- **{{class_id}}**{% if class_def.subclass_of %} (subclass of {{class_def.subclass_of}}){% endif %}{% if class_def.comment %}: {{class_def.comment}}{% endif %}
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{% endfor %}
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## Object Properties (connect entities):
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{% for prop_id, prop_def in object_properties.items() %}
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- **{{prop_id}}**{% if prop_def.domain and prop_def.range %} ({{prop_def.domain}} → {{prop_def.range}}){% endif %}{% if prop_def.comment %}: {{prop_def.comment}}{% endif %}
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{% endfor %}
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## Datatype Properties (entity attributes):
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{% for prop_id, prop_def in datatype_properties.items() %}
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- **{{prop_id}}**{% if prop_def.domain and prop_def.range %} ({{prop_def.domain}} → {{prop_def.range}}){% endif %}{% if prop_def.comment %}: {{prop_def.comment}}{% endif %}
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{% endfor %}
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## Text to Analyze:
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{{text}}
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## Extraction Rules:
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1. Only use classes defined above for entity types
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2. Only use properties defined above for relationships and attributes
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3. Respect domain and range constraints where specified
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4. For class instances, use `rdf:type` as the predicate
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5. Include `rdfs:label` for new entities to provide human-readable names
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6. Extract all relevant triples that can be inferred from the text
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7. Use entity URIs or meaningful identifiers as subjects/objects
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## Output Format:
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Return ONLY a valid JSON array (no markdown, no code blocks) containing objects with these fields:
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- "subject": the subject entity (URI or identifier)
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- "predicate": the property (from ontology or rdf:type/rdfs:label)
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- "object": the object entity or literal value
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Important: Return raw JSON only, with no markdown formatting, no code blocks, and no backticks.
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## Example Output:
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[
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{"subject": "recipe:cornish-pasty", "predicate": "rdf:type", "object": "Recipe"},
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{"subject": "recipe:cornish-pasty", "predicate": "rdfs:label", "object": "Cornish Pasty"},
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{"subject": "recipe:cornish-pasty", "predicate": "has_ingredient", "object": "ingredient:flour"},
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{"subject": "ingredient:flour", "predicate": "rdf:type", "object": "Ingredient"},
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{"subject": "ingredient:flour", "predicate": "rdfs:label", "object": "plain flour"}
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]
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Now extract triples from the text above.
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