Triple
T8732251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cesca Chair |
E207284
|
entity |
| Predicate | hasTypicalSeatColor |
P84338
|
FINISHED |
| Object | natural cane |
—
|
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: natural cane | Statement: [Cesca Chair, hasTypicalSeatColor, natural cane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalSeatColor Context triple: [Cesca Chair, hasTypicalSeatColor, natural cane]
-
A.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
B.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
C.
typicalSeat
Indicates the usual or standard seating position or location associated with an entity in a given context.
-
D.
hasInteriorColor
Indicates that an entity possesses a specific color used on its interior surfaces or internal parts.
-
E.
hasBermSeating
Indicates that a venue or location includes berm-style seating areas, typically grass-covered embankments where spectators can sit.
- F. None of above. chosen
Provenance (4 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d2903b08190a5ef29b6d6ca5f1c |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc489dd528819084ed5d88bd8bb3d6 |
completed | March 31, 2026, 10:20 p.m. |
Created at: March 30, 2026, 6:37 p.m.