Triple
T10372657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbus metropolitan area |
E244422
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Bexley, Ohio |
E312778
|
NE FINISHED |
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: Bexley, Ohio | Statement: [Columbus metropolitan area, containsCity, Bexley, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bexley, Ohio Context triple: [Columbus metropolitan area, containsCity, Bexley, Ohio]
-
A.
Bexley, Ohio
chosen
Bexley, Ohio is a small, affluent suburban city near downtown Columbus known for its historic homes, tree-lined streets, and institutions like Capital University.
-
B.
Bellevue, Ohio
Bellevue, Ohio is a small city in north-central Ohio known for its railroad heritage and location spanning multiple counties.
-
C.
Bedford, Ohio
Bedford, Ohio is a small suburban city in Cuyahoga County that forms part of the Greater Cleveland metropolitan area.
-
D.
Bryan, Ohio
Bryan, Ohio is a small city in northwestern Ohio that serves as the county seat of Williams County.
-
E.
Brooklyn, Ohio
Brooklyn, Ohio is a small suburban city located just west of Cleveland in Cuyahoga County.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e97f8a148190bb04996132cd464a |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d979ecfef48190a6014601bcddf761 |
completed | April 10, 2026, 10:30 p.m. |
Created at: April 6, 2026, 12:02 p.m.