Triple
T28173874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North America and Africa |
E715534
|
entity |
| Predicate | linkedByMajorAirHubsIn |
P180938
|
FINISHED |
| Object | New York City |
—
|
NE NERFINISHED |
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: New York City | Statement: [North America and Africa, linkedByMajorAirHubsIn, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedByMajorAirHubsIn Context triple: [North America and Africa, linkedByMajorAirHubsIn, New York City]
-
A.
associatedAirportPrimaryHubFor
Indicates that an airport serves as the primary hub for a particular airline or transportation operator.
-
B.
associatedHubAirport
Indicates that one entity serves as a primary or hub airport functionally linked to the other entity.
-
C.
airlineHub
Indicates that a particular location (typically an airport or city) serves as a central hub or primary operational base for an airline.
-
D.
secondaryHubOfAirline
Indicates that an airport serves as a secondary operational hub for a particular airline, supporting but not replacing its primary hub activities.
-
E.
otherMajorHub
Indicates that an entity is another primary hub or central node within the same network or system as the reference entity.
- F. None of above. chosen
Provenance (4 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_69efd6b340f0819095680e15dcdc1830 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f75dc25fa08190b371faf36d9fb72c |
completed | May 3, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f758586534819083e91172f4bf5098 |
completed | May 3, 2026, 2:14 p.m. |
| PDg | Predicate description generation | batch_69f75dc140c4819085063d6c4c36ca61 |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 27, 2026, 10:14 p.m.