Triple

T1030763
Position Surface form Disambiguated ID Type / Status
Subject Kimvita E22244 entity
Predicate spokenIn P2266 FINISHED
Object Kilifi County E121441 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: Kilifi County | Statement: [Kimvita, spokenIn, Kilifi County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kilifi County
Context triple: [Kimvita, spokenIn, Kilifi County]
  • A. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • B. Kigoma Region
    Kigoma Region is a western Tanzanian administrative region along Lake Tanganyika, known for its biodiversity and as a center for primate research.
  • C. Coast Province, Kenya chosen
    Coast Province, Kenya was a former administrative region along Kenya’s Indian Ocean coastline, known for its historic Swahili culture, major port city of Mombasa, and popular beach tourism.
  • D. Nakuru
    Nakuru is a prominent Kenyan city in the Rift Valley region, known for its proximity to Lake Nakuru National Park and its role as an important agricultural and commercial center.
  • E. Kigoma
    Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
  • 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b810429081908a97014ca740824b completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac429675bc8190b2467ac86c41c3b5 completed March 7, 2026, 3:21 p.m.
Created at: March 1, 2026, 7:41 p.m.