Triple

T21245825
Position Surface form Disambiguated ID Type / Status
Subject Wisconsin's 4th congressional district E523604 entity
Predicate cityIncluded P3207 FINISHED
Object Wauwatosa NE NERFINISHED

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: Wauwatosa | Statement: [Wisconsin's 4th congressional district, cityIncluded, Wauwatosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wauwatosa
Context triple: [Wisconsin's 4th congressional district, cityIncluded, Wauwatosa]
  • A. Wauwatosa chosen
    Wauwatosa is a suburban city in Milwaukee County, Wisconsin, known for its residential neighborhoods, commercial districts, and proximity to Milwaukee.
  • B. 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.
  • C. Oconomowoc
    Oconomowoc is a small lakeside city in southeastern Wisconsin known for its scenic waterfronts and historic downtown.
  • D. West Bend, Wisconsin
    West Bend, Wisconsin is a small city in southeastern Wisconsin known for its historic downtown, access to Kettle Moraine natural areas, and role as a regional commercial and cultural center.
  • E. Kenosha
    Kenosha is a mid-sized city in southeastern Wisconsin located on the shore of Lake Michigan between Milwaukee and Chicago.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b513b89c81908b27147e91368db2 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73599e5548190ad70d2c2bfa9e919 completed April 21, 2026, 8:30 a.m.
Created at: April 16, 2026, 3:49 p.m.