Triple

T21765928
Position Surface form Disambiguated ID Type / Status
Subject Taylors E537291 entity
Predicate hasISO3166-2Code P208 FINISHED
Object US-SC 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: US-SC | Statement: [Taylors, hasISO3166-2Code, US-SC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: US-SC
Context triple: [Taylors, hasISO3166-2Code, US-SC]
  • A. SC State
    SC State is a public, historically Black land-grant university located in Orangeburg, South Carolina.
  • B. US-MS
    US-MS is the ISO 3166-2 code representing the U.S. state of Mississippi.
  • C. Carolinas
    The Carolinas are a region of the southeastern United States comprising the states of North Carolina and South Carolina.
  • D. South Carolina chosen
    South Carolina is a southeastern U.S. state known for its Atlantic coastline, historic cities like Charleston, and significant role in early American and Civil War history.
  • E. La Carolina
    La Carolina is a town and municipality in the province of Jaén in Andalusia, southern Spain, known historically as one of the New Towns of Sierra Morena founded in the 18th century.
  • 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_69e0c46f5d1c8190bf830409e98464e5 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f031a9a08c8190bc0588ffa0f2da44 completed April 28, 2026, 4:03 a.m.
Created at: April 16, 2026, 6:51 p.m.