Triple

T20133182
Position Surface form Disambiguated ID Type / Status
Subject Drew, Mississippi E490950 entity
Predicate locatedInCountrySubdivision P766 FINISHED
Object Sunflower County 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: Sunflower County | Statement: [Drew, Mississippi, locatedInCountrySubdivision, Sunflower County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sunflower County
Context triple: [Drew, Mississippi, locatedInCountrySubdivision, Sunflower County]
  • A. Sunflower County chosen
    Sunflower County is a rural county in the Mississippi Delta region of Mississippi, known for its agricultural economy and deep ties to blues and civil rights history.
  • B. Lamar County
    Lamar County is a county in the state of Georgia, United States, known for its seat in the city of Barnesville and its location in the central part of the state.
  • C. Lamar County
    Lamar County is a rural county in western Alabama known for its small communities and agricultural landscape.
  • D. Lamar County
    Lamar County is a county in northeastern Texas known for its seat in the city of Paris and its location near the Oklahoma border.
  • E. Rogers County
    Rogers County is a county in northeastern Oklahoma known for its county seat of Claremore and its mix of suburban communities and rural landscapes.
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66763ee908190af64af31b4ca2377 completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:32 p.m.