Triple

T8693949
Position Surface form Disambiguated ID Type / Status
Subject KNSE E206358 entity
Predicate county P75 FINISHED
Object Santa Rosa County E6400 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: Santa Rosa County | Statement: [KNSE, county, Santa Rosa County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Rosa County
Context triple: [KNSE, county, Santa Rosa County]
  • A. Bay County
    Bay County is a coastal county in the Florida Panhandle known for its Gulf of Mexico beaches and the city of Panama City.
  • B. Walton County
    Walton County is a coastal county in the Florida Panhandle known for its white-sand beaches, upscale beach communities, and location along the Gulf of Mexico.
  • C. Santa Rosa County, Florida chosen
    Santa Rosa County, Florida is a county in the Florida Panhandle known for its Gulf Coast beaches, military presence, and rapidly growing communities near Pensacola.
  • D. Sumter County
    Sumter County is a largely rural county in west-central Georgia known for its agricultural economy and the city of Americus as its county seat.
  • E. Sumter County
    Sumter County is a rural county in western Alabama known for its agricultural landscape, small communities, and location along the Mississippi state line.
  • 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_69ca835481fc819084e33d3bc883bfa6 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5826bbb48190a212fb1bb06e05e6 completed March 31, 2026, 11:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19f4a2bd881909745f349d847ca87 completed April 4, 2026, 11:31 p.m.
Created at: March 30, 2026, 6:33 p.m.