Triple
T2603853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LS |
E58608
|
entity |
| Predicate | airlinePrimaryMarket |
P15154
|
FINISHED |
| Object | leisure travel |
—
|
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: leisure travel | Statement: [LS, airlinePrimaryMarket, leisure travel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlinePrimaryMarket Context triple: [LS, airlinePrimaryMarket, leisure travel]
-
A.
mainAirlineFocus
Indicates that an airline is the primary or central focus of attention, operations, or analysis in a given context.
-
B.
primaryAirlinePartner
Indicates that one airline serves as the main or preferred partner airline for another entity, such as a traveler, company, or loyalty program.
-
C.
airlineType
chosen
Indicates the classification or category of an airline based on its operational or service characteristics.
-
D.
airlineCategory
Indicates the classification or type of an airline within a defined categorization system (e.g., full-service, low-cost, regional).
-
E.
airline
Indicates that an entity operates as a commercial air transport carrier providing flight services between locations.
- 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8def9bc8190b2e013abffc7b191 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd80ab7248190ba06ba14fe4c5638 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:49 p.m.