Triple
T16420522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenosha Public Museum |
E398805
|
entity |
| Predicate | operatedBy |
P86
|
FINISHED |
| Object | City of Kenosha |
E90911
|
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: City of Kenosha | Statement: [Kenosha Public Museum, operatedBy, City of Kenosha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Kenosha Context triple: [Kenosha Public Museum, operatedBy, City of Kenosha]
-
A.
City of Wauwatosa
The City of Wauwatosa is a suburban municipality in southeastern Wisconsin known for its residential neighborhoods, commercial districts, and proximity to Milwaukee.
-
B.
Kenosha
chosen
Kenosha is a mid-sized city in southeastern Wisconsin located on the shore of Lake Michigan between Milwaukee and Chicago.
-
C.
City of Kewaunee
The City of Kewaunee is a small lakeside community in northeastern Wisconsin situated on the shore of Lake Michigan and serving as the county seat of Kewaunee County.
-
D.
City of Madison
The City of Madison is the capital of Wisconsin, known for its lakeside setting, major public university, and vibrant civic and cultural life.
-
E.
Kaukauna, Wisconsin
Kaukauna, Wisconsin is a small industrial city on the Fox River known historically for its paper mills and hydroelectric power.
- 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e328f5c1bc8190a679f35bd6c0bc97 |
completed | April 18, 2026, 6:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ecfd99c8190a4375a0f62aa50d1 |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5:09 a.m.