Triple
T12497136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Williams County, Ohio |
E298720
|
entity |
| Predicate | hasCountySeat |
P383
|
FINISHED |
| Object | Bryan, Ohio |
E220957
|
NE 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: Bryan, Ohio | Statement: [Williams County, Ohio, hasCountySeat, Bryan, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bryan, Ohio Context triple: [Williams County, Ohio, hasCountySeat, Bryan, Ohio]
-
A.
Bryan, Ohio
chosen
Bryan, Ohio is a small city in northwestern Ohio that serves as the county seat of Williams County.
-
B.
Brunswick, Ohio
Brunswick, Ohio is a suburban city in Medina County that forms part of the Greater Cleveland metropolitan area.
-
C.
Dublin, Ohio
Dublin, Ohio is a suburban city northwest of Columbus known for its affluent neighborhoods, strong school system, and annual Dublin Irish Festival.
-
D.
Sylvania, Ohio
Sylvania, Ohio is a suburban city near Toledo known for its residential communities, strong school system, and proximity to the Michigan border.
-
E.
Boardman, Ohio
Boardman, Ohio is a large suburban community and commercial hub near Youngstown in northeastern Ohio.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94df948308190ace333230a4a3b38 |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012ec19c508190912c3fe186f8a992 |
completed | May 11, 2026, 1:20 a.m. |
Created at: April 8, 2026, 9:57 p.m.