Triple

T14968831
Position Surface form Disambiguated ID Type / Status
Subject Jones County, Georgia E373262 entity
Predicate hasCountyCode P10086 FINISHED
Object Jones County E373262 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: Jones County | Statement: [Jones County, Georgia, hasCountyCode, Jones County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jones County
Context triple: [Jones County, Georgia, hasCountyCode, Jones County]
  • A. Jones County chosen
    Jones County is a county in central Georgia, United States, known for its rural character and proximity to the city of Macon.
  • B. Jones County
    Jones County is a rural county in the U.S. state of Texas, known for its agricultural economy and small communities near the Abilene region.
  • C. Jones County
    Jones County is a county in southeastern Mississippi known for its seat in Laurel and its historical role in the state's timber and agricultural industries.
  • D. Jones County
    Jones County is a county in eastern Iowa, United States, with Anamosa as its county seat.
  • E. Jones County
    Jones County is a rural county in eastern North Carolina known for its extensive forests, wetlands, and outdoor recreation areas.
  • 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_69d85ccbbcd48190acb56e7cf104d8ad completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6e44cb0819096e09f8026ef8174 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feef603b788190ad747d73af2363d4 completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 2:49 a.m.