Triple

T12211652
Position Surface form Disambiguated ID Type / Status
Subject Florence, South Carolina E290975 entity
Predicate county P75 FINISHED
Object Florence County E597816 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: Florence County | Statement: [Florence, South Carolina, county, Florence County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florence County
Context triple: [Florence, South Carolina, county, Florence County]
  • A. Florence County chosen
    Florence County is a county in northeastern South Carolina known for its regional hub city of Florence and its location along major transportation routes including Interstate 95.
  • B. Ware County
    Ware County is a county in southeastern Georgia known for encompassing much of the Okefenokee Swamp and having Waycross as its county seat.
  • C. Turner County
    Turner County is a rural county in southeastern South Dakota that forms part of the Sioux Falls metropolitan region.
  • D. McIntosh County
    McIntosh County is a coastal county in southeastern Georgia known for its marshlands, historic communities, and location along the Atlantic Intracoastal Waterway.
  • E. Laurens County
    Laurens County is a county in northwestern South Carolina known for its historic towns, rural landscapes, and role in the broader Upstate region’s textile and agricultural heritage.
  • 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_69d6ab65923081909acfc61b7a612233 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c915f548190b34a743f0a3bb51a completed April 10, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a9f45108190a814cdca52e77b5e completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:51 p.m.