Triple
T5936295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armani Teatro |
E132052
|
entity |
| Predicate | interiorCharacter |
P5509
|
FINISHED |
| Object | monochromatic palette |
—
|
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: monochromatic palette | Statement: [Armani Teatro, interiorCharacter, monochromatic palette]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interiorCharacter Context triple: [Armani Teatro, interiorCharacter, monochromatic palette]
-
A.
hasInteriorFeature
Indicates that an entity contains or includes a specific feature within its interior space.
-
B.
interiorStyle
chosen
Indicates that one entity has a particular interior design style or aesthetic characterized by the other entity.
-
C.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
D.
interiorFloor
Indicates that one entity is the interior floor surface or flooring of another enclosing space or structure.
-
E.
fieldOfOccupant
Indicates the specific professional or academic field in which an occupant is engaged or associated.
- 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_69c0085c55dc8190aa90e242c956e2fa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03f26f51881908cc253fe5775a1fc |
completed | March 22, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69c03355caf08190b960563a1aed23f9 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:01 p.m.