Triple
T17411900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SR 13 |
E423385
|
entity |
| Predicate | terminusB |
P388
|
FINISHED |
| Object | Huron, Ohio |
—
|
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: Huron, Ohio | Statement: [SR 13, terminusB, Huron, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huron, Ohio Context triple: [SR 13, terminusB, Huron, Ohio]
-
A.
Huron, Ohio
chosen
Huron, Ohio is a small city on the southern shore of Lake Erie known for its waterfront, marinas, and proximity to regional attractions like Cedar Point.
-
B.
Hudson, Ohio
Hudson, Ohio is a small city in northeastern Ohio known for its historic New England–style downtown and as a center of education and culture in the region.
-
C.
Wakeman, Ohio
Wakeman, Ohio is a small village in northern Ohio known for its rural character and location within Huron County.
-
D.
Holland, Ohio
Holland, Ohio is a small suburban village near Toledo known for its residential communities, local parks, and role as part of the greater Lucas County metropolitan area.
-
E.
Herrington, Ohio
Herrington, Ohio is a fictional small American town that serves as the primary setting for Zeke Tyler’s story.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b0b56788190ba012788f32afb78 |
completed | April 19, 2026, 2:16 a.m. |
Created at: April 10, 2026, 5:46 a.m.