Triple

T2223684
Position Surface form Disambiguated ID Type / Status
Subject Michael S. Barr E48597 entity
Predicate workLocation P7 FINISHED
Object Ann Arbor, Michigan 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, Michigan | Statement: [Michael S. Barr, workLocation, Ann Arbor, Michigan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ann Arbor, Michigan
Context triple: [Michael S. Barr, workLocation, Ann Arbor, Michigan]
  • 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. Berkley, Michigan
    Berkley, Michigan is a small suburban city in Oakland County known for its tree-lined neighborhoods, family-friendly community, and proximity to Detroit.
  • C. East Lansing
    East Lansing is a city in central Michigan best known as the home of Michigan State University.
  • D. Portland, Michigan
    Portland, Michigan is a small city in Ionia County known for its historic downtown, multiple riverfront parks, and extensive network of pedestrian bridges and trails.
  • E. Grand Rapids, Michigan
    Grand Rapids, Michigan is a mid-sized city in western Michigan known for its strong Dutch-American heritage, vibrant arts scene, and historic furniture manufacturing 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_69a88aa51b388190949868ec9766e587 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc03d1df88190950c691a4c246bd1 completed March 7, 2026, 6:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69af176447d881909173c62cc8c394a0 completed March 9, 2026, 6:54 p.m.
Created at: March 4, 2026, 7:47 p.m.