Triple

T18311066
Position Surface form Disambiguated ID Type / Status
Subject University of Wisconsin–Platteville E438624 entity
Predicate city P40 FINISHED
Object Platteville 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: Platteville | Statement: [University of Wisconsin–Platteville, city, Platteville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Platteville
Context triple: [University of Wisconsin–Platteville, city, Platteville]
  • A. Platteville, Wisconsin chosen
    Platteville, Wisconsin is a small city in southwestern Wisconsin known for the University of Wisconsin–Platteville and its strong college basketball tradition.
  • B. Plattville
    Plattville is a small village located in Kendall County, Illinois, United States.
  • 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. Burlington, Wisconsin
    Burlington, Wisconsin is a small city in southeastern Wisconsin known for its historic downtown, chocolate festival, and location along the Fox River.
  • E. Belmont, Wisconsin
    Belmont, Wisconsin is a small village historically notable as the site of the first capital of the Wisconsin Territory.
  • 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_69d8b915e3e881909125d760c15d0c29 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50219cd548190b8da5f402d5da773 completed April 19, 2026, 4:26 p.m.
Created at: April 10, 2026, 10:36 a.m.