Triple
T19749137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashland College |
E474330
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Ashland, 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: Ashland, Ohio | Statement: [Ashland College, locatedIn, Ashland, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashland, Ohio Context triple: [Ashland College, locatedIn, Ashland, Ohio]
-
A.
Ashland, Ohio
chosen
Ashland, Ohio is a small city in north-central Ohio known historically as a regional manufacturing and agricultural center and home to Ashland University.
-
B.
Ashland
Ashland is an unincorporated community in Alameda County, California, situated in the East Bay region of the San Francisco Bay Area.
-
C.
Ashland
Ashland is a Chicago 'L' rapid transit station on the CTA's Pink Line serving the city's Near West Side.
-
D.
Ashland
Ashland is a city that serves as the home base for Ashland College’s men’s basketball team, known for its local collegiate sports presence.
-
E.
Ashland
Ashland is a small town in northern Mississippi that serves as the administrative and cultural center of Benton County.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65296fa80819085aa4a18153531cf |
completed | April 20, 2026, 4:21 p.m. |
Created at: April 10, 2026, 1:47 p.m.