Triple

T20226755
Position Surface form Disambiguated ID Type / Status
Subject Ralph Peace E495403 entity
Predicate workSetting P58315 FINISHED
Object Medallion, Ohio 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: Medallion, Ohio | Statement: [Ralph Peace, workSetting, Medallion, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Medallion, Ohio
Context triple: [Ralph Peace, workSetting, Medallion, Ohio]
  • A. Medallion, Ohio chosen
    Medallion, Ohio is the fictional small town in Toni Morrison’s novel "Sula," serving as the primary setting and social backdrop for the Black community known as the Bottom.
  • B. Medina, Ohio
    Medina, Ohio is a historic small city and county seat southwest of Cleveland, known for its preserved 19th-century town square and role as a suburban community within the Greater Cleveland area.
  • C. Richfield, Ohio
    Richfield, Ohio is a small village in Summit County known for its suburban-rural character and proximity to the Cuyahoga Valley National Park.
  • D. Woodmere, Ohio
    Woodmere, Ohio is a small suburban village in Cuyahoga County known for its upscale retail and commercial corridor along Chagrin Boulevard.
  • E. Moraine, Ohio
    Moraine, Ohio is a small industrial city near Dayton known for its history of automobile manufacturing and assembly plants.
  • 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_69da626cff80819097b530718a7c98b6 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66fda9428819098467e7e8c547a07 completed April 20, 2026, 6:26 p.m.
Created at: April 11, 2026, 11:39 p.m.