Triple
T24735200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rochester International Airport |
E618393
|
entity |
| Predicate | hasDistanceFromCityCenterMiles |
P1299
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Rochester International Airport, hasDistanceFromCityCenterMiles, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistanceFromCityCenterMiles Context triple: [Rochester International Airport, hasDistanceFromCityCenterMiles, 7]
-
A.
isFartherFromCityCenterThan
Indicates that one location is at a greater distance from the city center than another location.
-
B.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown area.
-
C.
distanceFromMajorCity
Indicates the measured distance between a given location and a specified major city.
-
D.
distance to Midtown Manhattan (miles)
Indicates the physical separation between a location and Midtown Manhattan, measured in miles.
-
E.
distanceFromHanaTown (miles)
Indicates the number of miles separating a given place or entity from Hana Town.
- 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_69e2fab772608190b74163751047ff50 |
completed | April 18, 2026, 3:29 a.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:03 a.m.