Triple
T8419337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Perth, New York |
E198807
|
entity |
| Predicate | isProximateTo |
P53174
|
FINISHED |
| Object | Adirondack Park boundary |
—
|
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: Adirondack Park boundary | Statement: [Town of Perth, New York, isProximateTo, Adirondack Park boundary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isProximateTo Context triple: [Town of Perth, New York, isProximateTo, Adirondack Park boundary]
-
A.
isCloseTo
Indicates that one entity is physically or conceptually near another, within a relatively short distance or range.
-
B.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
C.
closerTo
Indicates that one entity is at a smaller distance to a reference entity than another entity is.
-
D.
closestTo
Indicates that one entity is nearer in distance to a reference entity than any other comparable entity.
-
E.
proximityToLandmark
chosen
Indicates a spatial relationship where one entity is located near or close to a specified landmark.
- 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_69ca8312d63c8190bf133b676b44a385 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb84c941988190884a5c0cbb44bcc2 |
completed | March 31, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69cb70d70ea081909c3dc1bd2ec14f85 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:06 p.m.