Triple
T11830202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Enchanted Cottage |
E281367
|
entity |
| Predicate | portraysConcept |
P463
|
FINISHED |
| Object | beauty as a matter of perception |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: beauty as a matter of perception | Statement: [The Enchanted Cottage, portraysConcept, beauty as a matter of perception]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysConcept Context triple: [The Enchanted Cottage, portraysConcept, beauty as a matter of perception]
-
A.
portrayalFeature
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of another entity.
-
B.
conceptualizedFor
Indicates that one entity has been conceived, designed, or mentally framed specifically for use, application, or relevance to another entity.
-
C.
portraysPersonAs
Indicates that one entity represents, depicts, or characterizes another person in a particular way or role.
-
D.
featuredConcept
Indicates that one concept is highlighted or given special prominence relative to others in a particular context.
-
E.
demonstratedConcept
chosen
Indicates that an entity has shown, illustrated, or made evident a particular concept through example, explanation, or action.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62b75dc8190b27d24e46a262a11 |
completed | April 10, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_69d8a251fc08819095933f1d13c3b742 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.