Triple
T1374007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Endicott, New York |
E30177
|
entity |
| Predicate | hasCountySeatOf |
P27090
|
FINISHED |
| Object | none (not a county seat) |
—
|
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: none (not a county seat) | Statement: [Endicott, New York, hasCountySeatOf, none (not a county seat)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCountySeatOf Context triple: [Endicott, New York, hasCountySeatOf, none (not a county seat)]
-
A.
hasCountySeatOn
Indicates that a county’s administrative center (county seat) is located on or adjacent to a specified geographic feature or infrastructure.
-
B.
hasCountySeatFunction
Indicates that an entity serves as the official county seat, functioning as the administrative center for a county.
-
C.
hasCountySeatFeature
Indicates that a county has a specific feature serving as its official county seat (administrative center).
-
D.
isInCountySeatOf
Indicates that one entity is located within the town or city that serves as the administrative center (county seat) of a specified county.
-
E.
countySeat
Indicates that one place serves as the administrative center or capital of a county.
- F. None of above. chosen
Provenance (4 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2f660888190bc9240e0dc4f0aa3 |
completed | March 1, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69a4befcabdc8190a9f05d002603f81c |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c0335f7081908d50046ced4cdee0 |
completed | March 1, 2026, 10:39 p.m. |
Created at: March 1, 2026, 7:57 p.m.