Triple
T261688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Fifth Avenue store |
E5553
|
entity |
| Predicate | flagshipStatus |
P10071
|
FINISHED |
| Object | global flagship for Apple retail |
—
|
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: global flagship for Apple retail | Statement: [Apple Fifth Avenue store, flagshipStatus, global flagship for Apple retail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flagshipStatus Context triple: [Apple Fifth Avenue store, flagshipStatus, global flagship for Apple retail]
-
A.
flagshipProgram
Indicates that a program is the primary, most prominent, or most important offering associated with an entity.
-
B.
flagFlown
Indicates that a particular flag is being displayed or flown at a specific location or by a specific entity.
-
C.
fleetFlagshipOf
Indicates that one entity serves as the primary or leading flagship of a particular fleet.
-
D.
flag
Indicates that one entity marks, signals, or draws attention to another entity, often to denote status, importance, or the need for review or action.
-
E.
flagBearer
Indicates that one entity serves as the carrier or holder of a flag on behalf of another entity, group, or cause.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25e2aba74819093eddd8d820260c0 |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b6c968c819094fc903a3a377e15 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25e292fdc8190bfd51d8848f9ed58 |
completed | Feb. 28, 2026, 3:16 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.