Triple
T4937945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohio State Route 33 |
E110857
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object |
Logan, Ohio
Logan, Ohio is a small city in southeastern Ohio that serves as a gateway to the Hocking Hills region and its popular outdoor recreation areas.
|
E525748
|
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: Logan, Ohio | Statement: [Ohio State Route 33, connectsCity, Logan, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Logan, Ohio Context triple: [Ohio State Route 33, connectsCity, Logan, Ohio]
-
A.
Wakeman, Ohio
Wakeman, Ohio is a small village in northern Ohio known for its rural character and location within Huron County.
-
B.
New London, Ohio
New London, Ohio is a small village in Huron County known for its rural character and location in north-central Ohio.
-
C.
Lockbourne, Ohio
Lockbourne, Ohio is a small village in central Ohio that is part of the Columbus metropolitan area.
-
D.
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.
-
E.
Wapakoneta, Ohio
Wapakoneta, Ohio is a small city in western Ohio best known as the hometown of astronaut Neil Armstrong and for its strong ties to aerospace history.
- 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: Logan, Ohio Triple: [Ohio State Route 33, connectsCity, Logan, Ohio]
Generated description
Logan, Ohio is a small city in southeastern Ohio that serves as a gateway to the Hocking Hills region and its popular outdoor recreation areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Logan, Ohio Target entity description: Logan, Ohio is a small city in southeastern Ohio that serves as a gateway to the Hocking Hills region and its popular outdoor recreation areas.
-
A.
Wakeman, Ohio
Wakeman, Ohio is a small village in northern Ohio known for its rural character and location within Huron County.
-
B.
New London, Ohio
New London, Ohio is a small village in Huron County known for its rural character and location in north-central Ohio.
-
C.
Lockbourne, Ohio
Lockbourne, Ohio is a small village in central Ohio that is part of the Columbus metropolitan area.
-
D.
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.
-
E.
Wapakoneta, Ohio
Wapakoneta, Ohio is a small city in western Ohio best known as the hometown of astronaut Neil Armstrong and for its strong ties to aerospace history.
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70872270819080769dad972681ef |
completed | March 20, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf9ad2f8e48190aac71e657a9e1197 |
completed | March 22, 2026, 7:31 a.m. |
| NEDg | Description generation | batch_69bf9b9dbabc81908ef4d25455616f76 |
completed | March 22, 2026, 7:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf9c45029c8190b9588a436d9804af |
completed | March 22, 2026, 7:37 a.m. |
Created at: March 20, 2026, 1:31 p.m.