Triple
T5542139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Wisconsin |
E145314
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
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.
|
E528186
|
NE FINISHED |
How this triple was built (4 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: Stevens Point | Statement: [Central Wisconsin, contains, Stevens Point]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stevens Point Context triple: [Central Wisconsin, contains, Stevens Point]
-
A.
Kenosha
Kenosha is a mid-sized city in southeastern Wisconsin located on the shore of Lake Michigan between Milwaukee and Chicago.
-
B.
Racine
Racine is a city in southeastern Wisconsin located on the shore of Lake Michigan, known historically for its manufacturing industry and Danish kringle pastries.
-
C.
Racine
Racine is a Chicago Transit Authority Blue Line rapid transit station serving the Near West Side of Chicago.
-
D.
Racine
Racine is a renowned 17th-century French dramatist celebrated for his classical tragedies such as "Phèdre" and "Andromaque."
-
E.
De Pere, Wisconsin
De Pere, Wisconsin is a small city in Brown County along the Fox River, just south of Green Bay, known for its historic downtown and St. Norbert College.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Stevens Point Triple: [Central Wisconsin, contains, Stevens Point]
Generated description
Stevens Point is a small city in central Wisconsin known for its university, historic downtown, and access to outdoor recreation along the Wisconsin River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stevens Point Target entity description: Stevens Point is a small city in central Wisconsin known for its university, historic downtown, and access to outdoor recreation along the Wisconsin River.
-
A.
Kenosha
Kenosha is a mid-sized city in southeastern Wisconsin located on the shore of Lake Michigan between Milwaukee and Chicago.
-
B.
Racine
Racine is a city in southeastern Wisconsin located on the shore of Lake Michigan, known historically for its manufacturing industry and Danish kringle pastries.
-
C.
Racine
Racine is a Chicago Transit Authority Blue Line rapid transit station serving the Near West Side of Chicago.
-
D.
Racine
Racine is a renowned 17th-century French dramatist celebrated for his classical tragedies such as "Phèdre" and "Andromaque."
-
E.
De Pere, Wisconsin
De Pere, Wisconsin is a small city in Brown County along the Fox River, just south of Green Bay, known for its historic downtown and St. Norbert College.
- F. None of above. chosen
Provenance (5 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_69c008fa64888190adae56c8f9ea4031 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fc7e26481908cec8d0483170ea5 |
completed | March 22, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0281fb73881909df8e4f98b27ce1e |
completed | March 22, 2026, 5:34 p.m. |
| NEDg | Description generation | batch_69c033df2c7881909660eb931908318c |
completed | March 22, 2026, 6:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c034640cd081909b44ff23e9005e57 |
completed | March 22, 2026, 6:26 p.m. |
Created at: March 22, 2026, 3:35 p.m.