Triple

T28361281
Position Surface form Disambiguated ID Type / Status
Subject Kenya (former provinces system) E718367 entity
Predicate mappingToNewUnits P9923 FINISHED
Object provinces were split into multiple counties 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: provinces were split into multiple counties | Statement: [Kenya (former provinces system), mappingToNewUnits, provinces were split into multiple counties]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mappingToNewUnits
Context triple: [Kenya (former provinces system), mappingToNewUnits, provinces were split into multiple counties]
  • A. convertedUnit
    Indicates that one unit is the result of converting a quantity expressed in another unit.
  • B. conversionUse
    Indicates that one entity is used as a means, method, or context for converting another entity from one form, state, or representation to another.
  • C. someUnitsConvertedTo
    Indicates that a quantity expressed in one unit of measurement has been transformed into an equivalent quantity expressed in another unit.
  • D. mapsTo chosen
    Indicates that one entity is associated with or transformed into another entity, typically defining a directional correspondence or function from a source to a target.
  • E. mappingSource
    Indicates that one entity serves as the origin or provider of a mapping or correspondence that defines how elements relate between two representations or systems.
  • F. None of above.

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_69eff6ed5af48190be4e0adf298223e0 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64c3291888190a0f53f691269bbff completed May 2, 2026, 7:10 p.m.
PD Predicate disambiguation batch_69f641e2f1708190b45b48d6a43c51d2 completed May 2, 2026, 6:26 p.m.
Created at: April 28, 2026, 12:52 a.m.