Triple

T10565297
Position Surface form Disambiguated ID Type / Status
Subject Safari Golf Course E249332 entity
Predicate hasState P35 FINISHED
Object Ohio E30904 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: Ohio | Statement: [Safari Golf Course, hasState, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ohio
Context triple: [Safari Golf Course, hasState, Ohio]
  • A. Ohio chosen
    Ohio is a Midwestern U.S. state known for its diverse economy, major cities like Columbus, Cleveland, and Cincinnati, and its significant role in national politics as a historic swing state.
  • B. Indiana
    "Indiana" is a jazz standard widely performed and recorded by saxophonist Don Byas, showcasing his virtuosic improvisational style.
  • C. Indiana
    Indiana is a U.S. state known for its manufacturing base, rich agricultural land, and iconic events like the Indianapolis 500.
  • D. Michigan
    "Michigan" is an acclaimed 2003 indie folk concept album by Sufjan Stevens that explores the history, geography, and culture of the U.S. state of Michigan.
  • E. Michigan
    Michigan is a U.S. state in the Great Lakes region known for its extensive freshwater coastline, automotive industry heritage, and diverse forests and waterways.
  • 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5272c32c48190a92c1dacd4deb9fe completed April 7, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96b474a248190b46c31e8e0008f9f completed April 10, 2026, 9:27 p.m.
Created at: April 6, 2026, 12:36 p.m.