Triple
T18214855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wayne County Airport |
E436124
|
entity |
| Predicate | isIn |
P1393
|
FINISHED |
| Object | 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: Ohio | Statement: [Wayne County Airport, isIn, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ohio Context triple: [Wayne County Airport, isIn, Ohio]
-
A.
Ohio
chosen
Ohio is a Midwestern U.S. state known for its diverse economy, major cities like Columbus, Cleveland, and Cincinnati, and its significant role in national politics as a historic swing state.
-
B.
Indiana
"Indiana" is a jazz standard widely performed and recorded by saxophonist Don Byas, showcasing his virtuosic improvisational style.
-
C.
Indiana
Indiana is a U.S. state known for its manufacturing base, rich agricultural land, and iconic events like the Indianapolis 500.
-
D.
Michigan
"Michigan" is an acclaimed 2003 indie folk concept album by Sufjan Stevens that explores the history, geography, and culture of the U.S. state of Michigan.
-
E.
Michigan
Michigan is a U.S. state in the Great Lakes region known for its automotive industry centered in Detroit and its distinctive two-peninsula geography.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e476a6548190bda03190c5f531ad |
completed | April 19, 2026, 2:19 p.m. |
Created at: April 10, 2026, 10:32 a.m.