Triple

T22212612
Position Surface form Disambiguated ID Type / Status
Subject Oshkosh Recreation Gym E548991 entity
Predicate city P40 FINISHED
Object Oshkosh 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: Oshkosh | Statement: [Oshkosh Recreation Gym, city, Oshkosh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oshkosh
Context triple: [Oshkosh Recreation Gym, city, Oshkosh]
  • A. Oshkosh, Wisconsin chosen
    Oshkosh, Wisconsin is a city on the western shore of Lake Winnebago known for its historic manufacturing industry, the EAA AirVenture aviation festival, and its namesake OshKosh B’gosh clothing brand.
  • B. Rock Island
    Rock Island is a small, remote island in Lake Michigan known for its state park, historic lighthouse, and rustic natural setting accessible only by boat.
  • C. Rock Island
    Rock Island is a small city in central Washington State located along the Columbia River in Douglas County.
  • D. Manitowoc
    Manitowoc is a city in eastern Wisconsin on the shores of Lake Michigan, known historically for its shipbuilding and manufacturing industries.
  • E. Cudahy
    Cudahy is a suburban city in southeastern Wisconsin located just south of Milwaukee along the Lake Michigan shoreline.
  • 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_69e11e3f7e04819089806d81d5ac431e completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12b2c8b608190b0047af4ac91b023 completed April 28, 2026, 9:48 p.m.
Created at: April 16, 2026, 8:36 p.m.