Triple
T7462459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Companion Pass |
E176283
|
entity |
| Predicate | primaryTravelerEarnsPoints |
P32734
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Companion Pass, primaryTravelerEarnsPoints, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTravelerEarnsPoints Context triple: [Companion Pass, primaryTravelerEarnsPoints, true]
-
A.
associatedWithFrequentFlyerProgram
Indicates that an entity has a connection or involvement with a frequent flyer program, such as membership, participation, or affiliation.
-
B.
pointsEarnedFrom
Indicates the number of points that an entity has received as a result of another specified source, action, or event.
-
C.
earnsMorePointsThan
Indicates that one entity receives a greater number of points than another entity in a given context or comparison.
-
D.
mileageAccrual
chosen
Indicates the accumulation or earning of mileage (such as distance-based points or credits) as a result of certain actions or usage.
-
E.
hasNotableTraveler
Indicates that an entity is associated with a traveler who is considered notable or significant in some recognized way.
- 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_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d80ae08190ba383066cf0cb2ce |
completed | March 27, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69c6f03bad9c8190bdd5abb86d37df47 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:39 p.m.