Triple
T16142054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orange Township, Ohio |
E391681
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Orange, Ohio
Orange, Ohio is a small suburban village in Cuyahoga County known for its residential character and inclusion in the Greater Cleveland area.
|
E1196490
|
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: Orange, Ohio | Statement: [Orange Township, Ohio, hasPart, Orange, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orange, Ohio Context triple: [Orange Township, Ohio, hasPart, Orange, Ohio]
-
A.
Sylvania, Ohio
Sylvania, Ohio is a suburban city near Toledo known for its residential communities, strong school system, and proximity to the Michigan border.
-
B.
Ada, Ohio
Ada, Ohio is a small village in northwest Ohio best known as the home of Ohio Northern University.
-
C.
Orange Township, Ohio
Orange Township, Ohio is a small community in Cuyahoga County best known as the birthplace of U.S. President James A. Garfield.
-
D.
Hillsboro, Ohio
Hillsboro, Ohio is a small city in Highland County known as a regional hub for the surrounding rural communities of southwestern Ohio.
-
E.
Oxford, Ohio
Oxford, Ohio is a small college town in southwestern Ohio best known as the home of Miami University.
- 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: Orange, Ohio Triple: [Orange Township, Ohio, hasPart, Orange, Ohio]
Generated description
Orange, Ohio is a small suburban village in Cuyahoga County known for its residential character and inclusion in the Greater Cleveland area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Orange, Ohio Target entity description: Orange, Ohio is a small suburban village in Cuyahoga County known for its residential character and inclusion in the Greater Cleveland area.
-
A.
Sylvania, Ohio
Sylvania, Ohio is a suburban city near Toledo known for its residential communities, strong school system, and proximity to the Michigan border.
-
B.
Ada, Ohio
Ada, Ohio is a small village in northwest Ohio best known as the home of Ohio Northern University.
-
C.
Orange Township, Ohio
Orange Township, Ohio is a small community in Cuyahoga County best known as the birthplace of U.S. President James A. Garfield.
-
D.
Hillsboro, Ohio
Hillsboro, Ohio is a small city in Highland County known as a regional hub for the surrounding rural communities of southwestern Ohio.
-
E.
Oxford, Ohio
Oxford, Ohio is a small college town in southwestern Ohio best known as the home of Miami University.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d9082588190bc7e6ff491f0d94e |
completed | April 17, 2026, 11:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2b75988819094baaff8f53f48ce |
completed | May 10, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_69fff36d39f48190bb48a1821f08664a |
completed | May 10, 2026, 2:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fff3f2760c8190a58fedc2798614ae |
completed | May 10, 2026, 2:56 a.m. |
Created at: April 10, 2026, 5:01 a.m.