Triple

T6867844
Position Surface form Disambiguated ID Type / Status
Subject Kinnickinnic River E158456 entity
Predicate hasMouthIn P1008 FINISHED
Object Milwaukee E10031 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: Milwaukee | Statement: [Kinnickinnic River, hasMouthIn, Milwaukee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Milwaukee
Context triple: [Kinnickinnic River, hasMouthIn, Milwaukee]
  • A. Milwaukee chosen
    Milwaukee is the largest city in Wisconsin, known for its brewing traditions, industrial history, and location on the western shore of Lake Michigan.
  • B. Milwaukie
    Milwaukie is a small city in northwestern Oregon, located just south of Portland along the Willamette River.
  • C. Kenosha
    Kenosha is a mid-sized city in southeastern Wisconsin located on the shore of Lake Michigan between Milwaukee and Chicago.
  • D. Green Bay
    Green Bay is a small community located within the municipality of Northeastern Manitoulin and the Islands in Ontario, Canada.
  • E. Waukesha, Wisconsin
    Waukesha, Wisconsin is a suburban city west of Milwaukee known for its historic downtown, former mineral springs resorts, and location along the Fox River.
  • 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_69c68831e3648190a643c328122e4d43 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8a793a481909340239c065393a4 completed March 27, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7617847908190abacde0f816b4372 completed March 28, 2026, 5:04 a.m.
Created at: March 27, 2026, 2:21 p.m.