Triple

T20834548
Position Surface form Disambiguated ID Type / Status
Subject Elwana language E512923 entity
Predicate region P40 FINISHED
Object Kilifi 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: Kilifi County | Statement: [Elwana language, region, Kilifi County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kilifi County
Context triple: [Elwana language, region, Kilifi County]
  • A. Kilifi County chosen
    Kilifi County is an administrative region along Kenya’s Indian Ocean coast, known for its beaches, Swahili culture, and tourism-centered economy.
  • B. Mombasa County
    Mombasa County is a coastal administrative region of Kenya that encompasses the city of Mombasa and serves as a major hub for tourism, trade, and maritime activities along the Indian Ocean.
  • C. Kisumu County
    Kisumu County is a county in western Kenya along Lake Victoria, known as a major economic and political hub and the location of the city of Kisumu.
  • D. Kitui County
    Kitui County is a semi-arid administrative region in eastern Kenya known for its rural economy, coal deposits, and location between the coastal and central highland areas.
  • E. Migori County
    Migori County is an administrative region in southwestern Kenya known for its diverse ethnic communities, agriculture, and proximity to Lake Victoria and the Tanzanian border.
  • 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_69e0b4cf62a88190bbf92351e9e57259 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c32554648190bd66ac99b3a9072b completed April 21, 2026, 12:21 a.m.
Created at: April 16, 2026, 12:42 p.m.