Triple

T12000902
Position Surface form Disambiguated ID Type / Status
Subject Cleveland, Georgia E285656 entity
Predicate hasName P744 FINISHED
Object Cleveland E285656 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 | Statement: [Cleveland, Georgia, hasName, Cleveland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cleveland
Context triple: [Cleveland, Georgia, hasName, Cleveland]
  • A. Cleveland chosen
    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 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.
  • D. Cleveland
    Cleveland is a fictional character who serves as the central protagonist in the story "The Pirate."
  • E. Cleveland
    Cleveland is a common English surname most prominently associated with Grover Cleveland, the 22nd and 24th president of the United States.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903c26d7881909b67a31d04882eb5 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6554ec69c8190ba9ffbaf220c44f4 completed May 2, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:46 p.m.