Triple
T2110365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huron County, Ohio |
E42486
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Wakeman, Ohio
Wakeman, Ohio is a small village in northern Ohio known for its rural character and location within Huron County.
|
E302525
|
NE FINISHED |
How this triple was built (4 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: Wakeman, Ohio | Statement: [Huron County, Ohio, containsSettlement, Wakeman, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wakeman, Ohio Context triple: [Huron County, Ohio, containsSettlement, Wakeman, Ohio]
-
A.
New London, Ohio
New London, Ohio is a small village in Huron County known for its rural character and location in north-central Ohio.
-
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.
Huron, Ohio
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.
-
D.
Riverside, Ohio
Riverside, Ohio is a suburban city in Montgomery County that forms part of the Dayton metropolitan area in southwestern Ohio.
-
E.
Willard, Ohio
Willard, Ohio is a small city in north-central Ohio known historically as a railroad town and for its agricultural and manufacturing industries.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wakeman, Ohio Triple: [Huron County, Ohio, containsSettlement, Wakeman, Ohio]
Generated description
Wakeman, Ohio is a small village in northern Ohio known for its rural character and location within Huron County.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wakeman, Ohio Target entity description: Wakeman, Ohio is a small village in northern Ohio known for its rural character and location within Huron County.
-
A.
New London, Ohio
New London, Ohio is a small village in Huron County known for its rural character and location in north-central Ohio.
-
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.
Huron, Ohio
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.
-
D.
Riverside, Ohio
Riverside, Ohio is a suburban city in Montgomery County that forms part of the Dayton metropolitan area in southwestern Ohio.
-
E.
Willard, Ohio
Willard, Ohio is a small city in north-central Ohio known historically as a railroad town and for its agricultural and manufacturing industries.
- F. None of above. chosen
Provenance (5 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb024ce88190a30e1320e53b82bc |
completed | March 7, 2026, 5:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe86f11108190a1987c1cee133d56 |
completed | March 10, 2026, 9:46 a.m. |
| NEDg | Description generation | batch_69afe9395e2081909140e8c464489a08 |
completed | March 10, 2026, 9:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b00009cb5c8190a42c100029d4917b |
completed | March 10, 2026, 11:27 a.m. |
Created at: March 4, 2026, 7:43 p.m.