Triple
T25626820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ilion, New York |
E642454
|
entity |
| Predicate | servedByAirportNearby |
P51581
|
FINISHED |
| Object | Griffiss International Airport |
—
|
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: Griffiss International Airport | Statement: [Ilion, New York, servedByAirportNearby, Griffiss International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedByAirportNearby Context triple: [Ilion, New York, servedByAirportNearby, Griffiss International Airport]
-
A.
nearbyAirportRelationship
Indicates that one location has an airport situated close enough to serve it conveniently, establishing a nearby-airport relationship between the two.
-
B.
associatedAirportServes
chosen
Indicates that a given airport provides service to, or is used by, the associated entity (such as a city, region, or facility).
-
C.
nearbyAirportAccess
Indicates that an entity has convenient access to an airport located within a short distance or travel time.
-
D.
servesAirport
Indicates that a transportation service or route provides access to and operates for a particular airport.
-
E.
nearestLargerAirport
Indicates that one airport is the closest geographically among all airports that are larger (e.g., by traffic or capacity) than a given reference airport.
- 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_69e77e7bd4548190a0c691b8a2f27ff1 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6cee45590819086e489bfccbe4ac3 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
Created at: April 21, 2026, 5:15 p.m.