Triple
T18074538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LATAM Airlines Chile (regional operations) |
E432520
|
entity |
| Predicate | servesPassengerSegment |
P27830
|
FINISHED |
| Object | leisure travelers |
—
|
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 travelers | Statement: [LATAM Airlines Chile (regional operations), servesPassengerSegment, leisure travelers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesPassengerSegment Context triple: [LATAM Airlines Chile (regional operations), servesPassengerSegment, leisure travelers]
-
A.
crewTransportSegment
Indicates a segment of a journey during which crew members are transported from one location to another.
-
B.
servesPassengerTrafficType
chosen
Indicates that a transportation facility or service accommodates a specified type or category of passenger traffic.
-
C.
formerPassengerService
Indicates that an entity previously provided passenger transportation services but no longer does so.
-
D.
isInPassengerService
Indicates that an entity (such as a vehicle, vessel, or aircraft) is currently being used to carry passengers as part of regular service.
-
E.
hasPassengerAirlineService
Indicates that a location or facility is served by scheduled passenger airline flights.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9f40c9881909294d538c026d486 |
completed | April 19, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69e3f90c652481908133a73106d78919 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:26 a.m.