Triple
T8337277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wisconsin Highway 23 |
E195819
|
entity |
| Predicate | connectsCommunity |
P12608
|
FINISHED |
| Object | Sheboygan |
E393073
|
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: Sheboygan | Statement: [Wisconsin Highway 23, connectsCommunity, Sheboygan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sheboygan Context triple: [Wisconsin Highway 23, connectsCommunity, Sheboygan]
-
A.
Sheboygan, Wisconsin
chosen
Sheboygan, Wisconsin is a city on the western shore of Lake Michigan known for its maritime heritage, bratwurst culture, and freshwater surfing.
-
B.
La Crosse
La Crosse is a mid-sized city in western Wisconsin known for its location along the Mississippi River, historic downtown, and regional educational and healthcare institutions.
-
C.
Eau Claire
Eau Claire is a central riverside neighborhood in Calgary, Alberta, known for its mixed-use developments, public plazas, and proximity to the Bow River and downtown core.
-
D.
Wisconsin Rapids
Wisconsin Rapids is a small city in central Wisconsin known historically for its paper industry and location along the Wisconsin River.
-
E.
Kenosha
Kenosha is a mid-sized city in southeastern Wisconsin located on the shore of Lake Michigan between Milwaukee and Chicago.
- 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_69ca82ecbdc481908a55cad8ca062d88 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fd5027c81909724f25aa30bbe58 |
completed | March 31, 2026, 8:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6ccf66d48190a457e0ea869b278e |
completed | April 2, 2026, 1:19 p.m. |
Created at: March 30, 2026, 5:57 p.m.