Triple
T19425437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MVP Gold |
E485967
|
entity |
| Predicate | travelClassCoverage |
P35839
|
FINISHED |
| Object | economy |
—
|
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: economy | Statement: [MVP Gold, travelClassCoverage, economy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelClassCoverage Context triple: [MVP Gold, travelClassCoverage, economy]
-
A.
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.
-
B.
travelScope
Indicates the extent or range within which travel is allowed, intended, or applicable for an entity or activity.
-
C.
offersClassOfTravel
chosen
Indicates that a service provider makes a particular class or tier of travel (e.g., economy, business, first) available as an option.
-
D.
coTraveler
Indicates that two or more entities are traveling together along (part of) the same journey or route.
-
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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63218772c8190a48b6cb01bd12b73 |
completed | April 20, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.