Triple
T4208529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flying Blue |
E93839
|
entity |
| Predicate | usesEarningUnit |
P32728
|
FINISHED |
| Object | miles |
—
|
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: miles | Statement: [Flying Blue, usesEarningUnit, miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesEarningUnit Context triple: [Flying Blue, usesEarningUnit, miles]
-
A.
mileEarningUnit
chosen
Indicates the unit or basis (e.g., per mile, per dollar) used to calculate or award mileage or points in a mileage-earning relationship.
-
B.
earnsRewardsCurrency
Indicates that an entity receives or accumulates a specified rewards currency as a result of some action, status, or relationship.
-
C.
minorUnitUsage
Indicates how a minor or subordinate unit is used or functions in relation to a larger or primary unit.
-
D.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
E.
usesCurrency
Indicates that one entity conducts its financial transactions or values using the monetary unit represented by the other 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_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:03 p.m.