Triple
T35932500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Livonia, New York |
E1039202
|
entity |
| Predicate | isNearRegion |
P141258
|
FINISHED |
| Object | Finger Lakes |
—
|
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: Finger Lakes | Statement: [Town of Livonia, New York, isNearRegion, Finger Lakes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNearRegion Context triple: [Town of Livonia, New York, isNearRegion, Finger Lakes]
-
A.
passesNearRegion
Indicates that one entity moves or extends along a path that comes close to, but does not necessarily enter, a specified region.
-
B.
hasRegionalCenterNearby
Indicates that a regional center is located in close proximity to the referenced entity.
-
C.
hasNearbyGeographicalArea
chosen
Indicates that one geographical area is located in close spatial proximity to another geographical area.
-
D.
isInSameRegionAs
Indicates that two entities are located within the same defined geographic or administrative region.
-
E.
nearbyRegionCharacterizedBy
Indicates that a region located nearby another entity is defined or distinguished by a particular characteristic, feature, or condition.
- 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_69f76e23e4688190a5369138755138bf |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ac23d1388190bdf9628b294943bd |
completed | May 3, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.