Triple
T14269102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Hill Cemetery |
E353728
|
entity |
| Predicate | hasNearbyCityCenterDistance |
P36605
|
FINISHED |
| Object | close to downtown Auburn, New York |
—
|
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: close to downtown Auburn, New York | Statement: [Fort Hill Cemetery, hasNearbyCityCenterDistance, close to downtown Auburn, New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyCityCenterDistance Context triple: [Fort Hill Cemetery, hasNearbyCityCenterDistance, close to downtown Auburn, New York]
-
A.
nearbyUrbanCenter
chosen
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
B.
nearestCityCenterDistance
Indicates the distance from a given location to the closest city center.
-
C.
hasCoordinateInCityCentreApprox
Indicates that an entity’s location is approximately within the central area of a city, based on its geographic coordinates.
-
D.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
E.
hasRegionalCenterNearby
Indicates that a regional center is located in close proximity to the referenced 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de657fe6708190b41de48c43cff647 |
completed | April 14, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a7d586c8190846ff242bbf5ac53 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.