Triple

T442039
Position Surface form Disambiguated ID Type / Status
Subject Michigan Wolverines football E10133 entity
Predicate campus P269 FINISHED
Object Ann Arbor E46153 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: Ann Arbor | Statement: [Michigan Wolverines football, campus, Ann Arbor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ann Arbor
Context triple: [Michigan Wolverines football, campus, Ann Arbor]
  • A. Ann Arbor chosen
    Ann Arbor is a vibrant college town in southeastern Michigan best known as the home of the University of Michigan and a center for education, research, and arts.
  • B. East Lansing
    East Lansing is a city in central Michigan best known as the home of Michigan State University.
  • C. Kalamazoo
    Kalamazoo is a mid-sized city in southwestern Michigan known for its historic downtown, educational institutions like Western Michigan University, and a legacy of manufacturing and craft beer.
  • D. Ypsilanti
    Ypsilanti is a city in southeastern Michigan known for Eastern Michigan University and its historic downtown and automotive heritage.
  • E. Dearborn
    Dearborn is a city in the Detroit metropolitan area best known as the longtime headquarters of the Ford Motor Company and a historic center of the American automotive industry.
  • 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_69a2e8465ef481909655c681b01e2986 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2ef42b4008190abed9d79926c7022 completed Feb. 28, 2026, 1:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4e0277eb08190984ff5bcb9f349a0 completed March 2, 2026, 12:56 a.m.
Created at: Feb. 28, 2026, 1:11 p.m.