Triple

T15683536
Position Surface form Disambiguated ID Type / Status
Subject Beloit College E377637 entity
Predicate city P40 FINISHED
Object Beloit E1055424 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: Beloit | Statement: [Beloit College, city, Beloit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beloit
Context triple: [Beloit College, city, Beloit]
  • A. Beloit, Wisconsin chosen
    Beloit, Wisconsin is a small industrial and college city in southern Wisconsin near the Illinois border, known for Beloit College and its historic downtown.
  • B. Kenosha
    Kenosha is a mid-sized city in southeastern Wisconsin located on the shore of Lake Michigan between Milwaukee and Chicago.
  • C. 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.
  • D. Peoria
    Peoria is a suburban city in the Phoenix metropolitan area of central Arizona, known for its rapid growth, residential communities, and recreational amenities.
  • E. Peoria
    The Peoria are a Native American people originally from the Illinois River valley and part of the Illinois (Illiniwek) Confederation.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f31b5b881908e46ecd9fc6048ab completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff997e13e4819080a39f59172ab99c completed May 9, 2026, 8:30 p.m.
Created at: April 10, 2026, 4:17 a.m.