Triple

T636247
Position Surface form Disambiguated ID Type / Status
Subject Wisconsin E16627 entity
Predicate hasMajorCity P316 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: [Wisconsin, hasMajorCity, Green Bay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Green Bay
Context triple: [Wisconsin, hasMajorCity, 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. 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. Madison
    Madison is a common English surname and given name, historically associated with U.S. President James Madison and now widely used as a first name, especially for girls.
  • D. Canton
    Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
  • E. Duluth
    Duluth is a major port city in northeastern Minnesota known for its shipping industry, scenic Lake Superior shoreline, and role as a regional transportation hub.
  • 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_69a4936be1c88190af56540324b57da7 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49ee667f08190a0332b8f6c569e1a completed March 1, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a65e30cdbc819085f3c22f2e5ebb88 completed March 3, 2026, 4:06 a.m.
Created at: March 1, 2026, 7:35 p.m.