Triple
T21189280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenwood County |
E522169
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Greenwood |
—
|
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: Greenwood | Statement: [Greenwood County, largestCity, Greenwood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greenwood Context triple: [Greenwood County, largestCity, Greenwood]
-
A.
Greenwood
Greenwood is a residential neighborhood within the town of Bicester in Oxfordshire, England.
-
B.
Greenwood
Greenwood is a residential neighborhood within the city of Wakefield in Middlesex County, Massachusetts.
-
C.
Greenwood
Greenwood is a small city in the Mississippi Delta region of the United States, historically known as a center of cotton production and civil rights–era activity.
-
D.
Greenwood
Greenwood is a small lakeside city in Minnesota situated along the shores of Lake Minnetonka.
-
E.
Greenwood
chosen
Greenwood is a small city in South Carolina that serves as the administrative and commercial hub of Greenwood 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e733350e588190a31467758a8afa5c |
completed | April 21, 2026, 8:20 a.m. |
Created at: April 16, 2026, 3:07 p.m.