Triple

T17465348
Position Surface form Disambiguated ID Type / Status
Subject Pere Marquette E425261 entity
Predicate stopsAt P6657 FINISHED
Object Bangor, Michigan 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: Bangor, Michigan | Statement: [Pere Marquette, stopsAt, Bangor, Michigan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangor, Michigan
Context triple: [Pere Marquette, stopsAt, Bangor, Michigan]
  • A. Bangor, Michigan chosen
    Bangor, Michigan is a small city in southwestern Michigan known for its agricultural surroundings and role as a local community hub.
  • B. Burlington, Michigan
    Burlington, Michigan is a small village in south-central Michigan known for its rural character and location within Calhoun County.
  • C. Hartford, Michigan
    Hartford, Michigan is a small city in southwestern Michigan known for its rural character, agricultural surroundings, and proximity to major regional transportation routes.
  • D. Hanover, Michigan
    Hanover, Michigan is a small rural village in south-central Michigan known for its close-knit community and location within Jackson County.
  • E. Williamsburg, Michigan
    Williamsburg, Michigan is an unincorporated community in Grand Traverse County known for its rural character and proximity to the Traverse City area in northern Michigan.
  • 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_69d889dbc2e88190b18ea6115e819258 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451a6c2e08190bca9de56ee2f5136 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:47 a.m.