Triple
T18727861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York–London |
E457952
|
entity |
| Predicate | isKeyCorporateTravelCorridor |
P90002
|
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: [New York–London, isKeyCorporateTravelCorridor, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isKeyCorporateTravelCorridor Context triple: [New York–London, isKeyCorporateTravelCorridor, true]
-
A.
hasCorporateFlightDepartments
Indicates that an entity maintains one or more internal departments responsible for managing and operating its corporate aircraft and related flight operations.
-
B.
servesBusinessTravel
Indicates that an entity provides services or accommodations specifically intended for business-related travel.
-
C.
isKeyFreightRoute
Indicates that a transportation route serves as a primary or strategically important corridor for moving freight.
-
D.
isTouristTransitPoint
Indicates that a location serves as a transit hub or intermediate stop primarily used by tourists while traveling between destinations.
-
E.
isBusinessRoute
chosen
Indicates that a route functions primarily for business-related travel or commercial purposes 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d74bd9881908cd314e68327c402 |
completed | April 20, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:50 a.m.