Triple

T10995009
Position Surface form Disambiguated ID Type / Status
Subject Harper Woods, Michigan E259840 entity
Predicate partOf P40 FINISHED
Object Metro Detroit E79668 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: Metro Detroit | Statement: [Harper Woods, Michigan, partOf, Metro Detroit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metro Detroit
Context triple: [Harper Woods, Michigan, partOf, Metro Detroit]
  • A. Metro Detroit chosen
    Metro Detroit is a major metropolitan area in southeastern Michigan centered on the city of Detroit, known for its automotive industry, manufacturing base, and cultural institutions.
  • B. Downtown Detroit
    Downtown Detroit is the central business district and cultural core of Detroit, Michigan, known for its skyscrapers, sports arenas, theaters, and revitalized riverfront.
  • C. Downriver Detroit
    Downriver Detroit is a suburban industrial and residential region south of Detroit along the Detroit River, encompassing several working-class communities.
  • D. Midtown Detroit
    Midtown Detroit is a central cultural and educational district in Detroit, Michigan, known for its museums, universities, and historic architecture.
  • E. Detroiters
    Detroiters is an American comedy television series that follows two inept but enthusiastic best friends running a small advertising agency in Detroit.
  • 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_69d6aa8a6a548190a750f944ccdc8064 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d795d59ebc8190baff1f50bdc46c1b completed April 9, 2026, 12:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3451451988190add2762b1e1be8ed completed April 18, 2026, 8:47 a.m.
Created at: April 8, 2026, 9:24 p.m.