Triple
T3677800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westchester County Airport |
E78036
|
entity |
| Predicate | distanceToManhattanMiles |
P2383
|
FINISHED |
| Object | approximately 33 |
—
|
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: approximately 33 | Statement: [Westchester County Airport, distanceToManhattanMiles, approximately 33]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToManhattanMiles Context triple: [Westchester County Airport, distanceToManhattanMiles, approximately 33]
-
A.
approximateGreatCircleDistanceMiles
Indicates the approximate distance, measured in miles, between two locations along the great-circle path on the surface of a sphere (typically the Earth).
-
B.
approximateLengthInMiles
Indicates the estimated distance or extent of something measured in miles.
-
C.
distanceToNewYorkCity
chosen
Indicates the spatial distance between a given entity’s location and New York City.
-
D.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
E.
cityBlock
Indicates that one entity is a city block that contains, is the location of, or is otherwise spatially associated with the other entity.
- 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_69ad85e18c1c8190be8aafb227f39f48 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4643cf08190b2d10ddf4aac7407 |
completed | March 8, 2026, 6:48 p.m. |
| PD | Predicate disambiguation | batch_69adb84be1fc81909721c871babb4633 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:25 p.m.