Triple
T10524497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Copa ConnectMiles Platinum |
E248261
|
entity |
| Predicate | travelBenefitCategory |
P81024
|
FINISHED |
| Object | airport experience enhancement |
—
|
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: airport experience enhancement | Statement: [Copa ConnectMiles Platinum, travelBenefitCategory, airport experience enhancement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelBenefitCategory Context triple: [Copa ConnectMiles Platinum, travelBenefitCategory, airport experience enhancement]
-
A.
airportBenefit
chosen
Indicates that one entity gains an advantage, profit, or positive impact from the existence, operation, or services of an airport.
-
B.
offersClassOfTravel
Indicates that a service provider makes a particular class or tier of travel (e.g., economy, business, first) available as an option.
-
C.
tourCategory
Indicates the classification or type of a tour (e.g., by theme, style, or purpose) that the tour belongs to.
-
D.
travelClassRelevance
Indicates the degree to which a particular travel class (e.g., economy, business) is pertinent or applicable within a given travel context or scenario.
-
E.
travelsOn
Indicates that an entity moves or journeys using a particular route, path, or mode of transportation.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509f4020c8190b78c49da086df757 |
completed | April 7, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69d4fb94fa10819091f585bab4379c6f |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:29 p.m.