Triple

T21289188
Position Surface form Disambiguated ID Type / Status
Subject Burleigh County E524740 entity
Predicate hasCountyNumberInNorthDakota P143602 FINISHED
Object 08 LITERAL 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: 08 | Statement: [Burleigh County, hasCountyNumberInNorthDakota, 08]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCountyNumberInNorthDakota
Context triple: [Burleigh County, hasCountyNumberInNorthDakota, 08]
  • A. hasCountyNumberInSouthDakota
    Indicates that an entity is associated with a specific officially assigned county number within the state of South Dakota.
  • B. hasCountyNumberInKansas
    Indicates that an entity is assigned a specific official county number within the state of Kansas.
  • C. hasCountyNumberInIndiana
    Indicates that a county is associated with its designated county number within the state of Indiana.
  • D. hasCountyNumberInNewHampshire
    Indicates that a county is assigned a specific official county number within the state of New Hampshire.
  • E. northernTerminusCounty
    Indicates that a county serves as the northern endpoint or terminus of a specified route, line, or feature.
  • F. None of above. chosen

Provenance (4 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_69e0b5171f6c8190a5d57201ede73811 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736d882408190a2300327cb73b7f6 completed April 21, 2026, 8:35 a.m.
PD Predicate disambiguation batch_69e61612ab748190a72b8703b938abcb completed April 20, 2026, 12:03 p.m.
PDg Predicate description generation batch_69e6190163448190a2404b396215c686 completed April 20, 2026, 12:16 p.m.
Created at: April 16, 2026, 4:03 p.m.