Triple
T9688509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carthage College |
E234476
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | 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: Kenosha | Statement: [Carthage College, locatedIn, Kenosha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenosha Context triple: [Carthage College, locatedIn, 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 small unincorporated community in northeastern California known for its rural character and proximity to the Sierra Nevada and Lassen National Forest.
-
D.
Wauwatosa
Wauwatosa is a suburban city in Milwaukee County, Wisconsin, known for its residential neighborhoods, commercial districts, and proximity to Milwaukee.
-
E.
Stevens Point
Stevens Point is a small city in central Wisconsin known for its university, historic downtown, and access to outdoor recreation along the Wisconsin River.
- 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_69ca84ca73208190957a900c8543bdcc |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d019d40819095059a4d6167900a |
completed | April 1, 2026, 10:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d59ab0b48190acc133cc806582cc |
completed | April 5, 2026, 3:23 a.m. |
Created at: March 30, 2026, 8:17 p.m.