Triple
T1031050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ochre Court |
E22250
|
entity |
| Predicate | hasInteriorStyle |
P5509
|
FINISHED |
| Object | lavish period interiors |
—
|
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: lavish period interiors | Statement: [Ochre Court, hasInteriorStyle, lavish period interiors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInteriorStyle Context triple: [Ochre Court, hasInteriorStyle, lavish period interiors]
-
A.
interiorStyle
chosen
Indicates that one entity has a particular interior design style or aesthetic characterized by the other entity.
-
B.
hasInteriorFeature
Indicates that an entity contains or includes a specific feature within its interior space.
-
C.
architecturalStyleOfSeat
Indicates the architectural style that characterizes a particular seat or seating structure.
-
D.
hasBodyColor
Indicates that an entity possesses a particular body color as one of its attributes.
-
E.
hasLivery
Indicates that one entity bears or displays the distinctive colors, markings, or branding (livery) associated with another entity.
- 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95d35888190a20593a278175df7 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b7276180819085c6b23501a6a6e0 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.