Triple

T15621067
Position Surface form Disambiguated ID Type / Status
Subject Wisconsin State Highway 57 E375552 entity
Predicate connectsCity P4245 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: [Wisconsin State Highway 57, connectsCity, Milwaukee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Milwaukee
Context triple: [Wisconsin State Highway 57, connectsCity, 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. Washington, Wisconsin
    Washington, Wisconsin is a small town located in Eau Claire County in the western part of the U.S. state of Wisconsin.
  • E. Wauwatosa
    Wauwatosa is a suburban city in Milwaukee County, Wisconsin, known for its residential neighborhoods, commercial districts, and proximity to Milwaukee.
  • 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9a95f08190b0013ba1428849d3 completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ec2f35c8190a96af080cd7b6d0e completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 4:13 a.m.