Triple

T1641897
Position Surface form Disambiguated ID Type / Status
Subject Green Bay Packers E35491 entity
Predicate location P40 FINISHED
Object Green Bay, Wisconsin E11575 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: Green Bay, Wisconsin | Statement: [Green Bay Packers, location, Green Bay, Wisconsin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Green Bay, Wisconsin
Context triple: [Green Bay Packers, location, Green Bay, Wisconsin]
  • A. Green Bay, Wisconsin chosen
    Green Bay, Wisconsin is a city in northeastern Wisconsin best known as the home of the NFL’s Green Bay Packers and one of the oldest continuously operating professional football franchises in the United States.
  • B. Milwaukie
    Milwaukie is a small city in northwestern Oregon, located just south of Portland along the Willamette River.
  • C. Milwaukee
    Milwaukee is the largest city in Wisconsin, known for its brewing traditions, industrial history, and location on the western shore of Lake Michigan.
  • D. Kenosha
    Kenosha is a mid-sized city in southeastern Wisconsin located on the shore of Lake Michigan between Milwaukee and Chicago.
  • E. 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.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a3e254081908b7c4a9dfeafc4f8 completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad6818c8288190af5307384f1c8080 completed March 8, 2026, 12:14 p.m.
Created at: March 4, 2026, 7:28 p.m.