Triple

T11426453
Position Surface form Disambiguated ID Type / Status
Subject Wisconsin Highway 50 E270762 entity
Predicate connectsCommunity P12608 FINISHED
Object Kenosha E90911 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: Kenosha | Statement: [Wisconsin Highway 50, connectsCommunity, Kenosha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kenosha
Context triple: [Wisconsin Highway 50, connectsCommunity, Kenosha]
  • A. Kenosha chosen
    Kenosha is a mid-sized city in southeastern Wisconsin located on the shore of Lake Michigan between Milwaukee and Chicago.
  • 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. Janesville
    Janesville is a small unincorporated community in northeastern California known for its rural character and proximity to the Sierra Nevada and Lassen National Forest.
  • D. Wauwatosa
    Wauwatosa is a suburban city in Milwaukee County, Wisconsin, known for its residential neighborhoods, commercial districts, and proximity to Milwaukee.
  • E. Stevens Point
    Stevens Point is a small city in central Wisconsin known for its university, historic downtown, and access to outdoor recreation along the Wisconsin 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_69d6aadeef688190874bcecd88b3dd9b completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d806c000b88190bfaa646b2dc424b7 completed April 9, 2026, 8:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e713309c208190bb5764b3b5ccf130 completed April 21, 2026, 6:03 a.m.
Created at: April 8, 2026, 9:35 p.m.