Triple
T32859350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | town of Osceola |
E840468
|
entity |
| Predicate | locatedInU.S.StateRegion |
P49826
|
FINISHED |
| Object | northern 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: northern New York | Statement: [town of Osceola, locatedInU.S.StateRegion, northern New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInU.S.StateRegion Context triple: [town of Osceola, locatedInU.S.StateRegion, northern New York]
-
A.
locatedInStateOrRegion
Indicates that one entity is geographically situated within the boundaries of a specified state or region.
-
B.
inUSStateRegion
chosen
Indicates that one entity is located within, or belongs to, a specific region of a U.S. state.
-
C.
USStateRegion
Indicates that a U.S. state is located within or belongs to a particular geographic region of the United States.
-
D.
stateOrRegion
Indicates that one entity is a state or region in which the other entity is located or with which it is associated.
-
E.
locatedInUSRegion
Indicates that one entity is geographically situated within a specified region of the United States.
- 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_69f34942465c819099b3fb47f9044f58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a032d9200448190a2adcc5ee48bff01 |
completed | May 12, 2026, 1:39 p.m. |
| PD | Predicate disambiguation | batch_6a032c9f41f08190b1c60b0afbbac01a |
completed | May 12, 2026, 1:35 p.m. |
Created at: May 1, 2026, 1:17 a.m.