Triple

T11082690
Position Surface form Disambiguated ID Type / Status
Subject Cleveland Metroparks E262041 entity
Predicate headquartersLocation P62 FINISHED
Object Cleveland, Ohio E6554 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: Cleveland, Ohio | Statement: [Cleveland Metroparks, headquartersLocation, Cleveland, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cleveland, Ohio
Context triple: [Cleveland Metroparks, headquartersLocation, Cleveland, Ohio]
  • A. Cleveland
    Cleveland is a small city in northeastern Georgia known as a gateway to the Appalachian Mountains and nearby gold-mining and outdoor recreation areas.
  • B. Cleveland
    Cleveland is a historic industrial and coastal area in North East England, traditionally associated with ironstone mining and steelmaking.
  • C. Cleveland
    Cleveland is a common English surname most prominently associated with Grover Cleveland, the 22nd and 24th president of the United States.
  • D. Cleveland chosen
    Cleveland is a major city in the U.S. state of Ohio, known for its industrial history, cultural institutions like the Rock and Roll Hall of Fame, and its location on the southern shore of Lake Erie.
  • E. Cleveland
    Cleveland is a fictional character who serves as the central protagonist in the story "The Pirate."
  • 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_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799bf89f48190889f08d2f5dd220a completed April 9, 2026, 12:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58ac418f08190b2936e8dbf9fb27d completed April 20, 2026, 2:09 a.m.
Created at: April 8, 2026, 9:27 p.m.