Triple

T4592221
Position Surface form Disambiguated ID Type / Status
Subject Lambeau Field E103518 entity
Predicate city P40 FINISHED
Object Green Bay 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 | Statement: [Lambeau Field, city, Green Bay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Green Bay
Context triple: [Lambeau Field, city, Green Bay]
  • 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_69bd43dccaf08190aa89e9991a289719 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd592520ec8190b1bd4cb4d9b94c94 completed March 20, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa3f792881908f7d0bc1f09d517e completed March 21, 2026, 1:54 a.m.
Created at: March 20, 2026, 1:11 p.m.