Triple
T18622009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodmere, Ohio |
E455174
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Orange, 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: Orange, Ohio | Statement: [Woodmere, Ohio, adjacentTo, Orange, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orange, Ohio Context triple: [Woodmere, Ohio, adjacentTo, Orange, Ohio]
-
A.
Orange, Ohio
chosen
Orange, Ohio is a small suburban village in Cuyahoga County known for its residential character and inclusion in the Greater Cleveland area.
-
B.
Sylvania, Ohio
Sylvania, Ohio is a suburban city near Toledo known for its residential communities, strong school system, and proximity to the Michigan border.
-
C.
Ada, Ohio
Ada, Ohio is a small village in northwest Ohio best known as the home of Ohio Northern University.
-
D.
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.
-
E.
Hillsboro, Ohio
Hillsboro, Ohio is a small city in Highland County known as a regional hub for the surrounding rural communities of southwestern Ohio.
- 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54f020fa08190bd78d72182496b19 |
completed | April 19, 2026, 9:54 p.m. |
Created at: April 10, 2026, 11:46 a.m.