Triple
T23087952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenosha Unified School District |
E575663
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Kenosha |
—
|
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: Kenosha | Statement: [Kenosha Unified School District, city, Kenosha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenosha Context triple: [Kenosha Unified School District, city, Kenosha]
-
A.
Kenosha
chosen
Kenosha is a mid-sized city in southeastern Wisconsin located on the shore of Lake Michigan between Milwaukee and Chicago.
-
B.
Milwaukee
Milwaukee is the largest city in Wisconsin, known for its brewing traditions, industrial history, and location on the western shore of Lake Michigan.
-
C.
Janesville
Janesville is a city in southern Wisconsin known as an industrial and commercial hub along the Rock River.
-
D.
Janesville
Janesville is a small unincorporated community in northeastern California known for its rural character and proximity to the Sierra Nevada and Lassen National Forest.
-
E.
Washington, Wisconsin
Washington, Wisconsin is a small town located in Eau Claire County in the western part of the U.S. state of Wisconsin.
- 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_69e245bf3e3c819086d3448720efc01b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18da7c54c81908b62d04ab1811b06 |
completed | April 29, 2026, 4:48 a.m. |
Created at: April 17, 2026, 3:57 p.m.