Triple

T15836430
Position Surface form Disambiguated ID Type / Status
Subject Marsabit County E383996 entity
Predicate capital P234 FINISHED
Object Marsabit E1196185 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: Marsabit | Statement: [Marsabit County, capital, Marsabit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marsabit
Context triple: [Marsabit County, capital, Marsabit]
  • A. Marsabit chosen
    Marsabit is a remote market and administrative town in northern Kenya, known as a gateway to Marsabit National Park and its surrounding arid highlands.
  • B. Isiolo
    Isiolo is a town in central Kenya that serves as a key transport and commercial hub linking the country’s northern regions with the rest of the nation.
  • C. Kajiado
    Kajiado is a town in southern Kenya that serves as an administrative and commercial center for the surrounding Maasai-inhabited region.
  • D. Wazaramo
    Wazaramo are a Bantu-speaking ethnic group native to the coastal and near-coastal regions around Dar es Salaam in eastern Tanzania.
  • E. 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.
  • 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_69d86da34c888190976e06c4019d415a completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e142e1fcd48190bcb884f6c65db847 completed April 16, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69fffee4f84c81908b2c7e216ef159e0 completed May 10, 2026, 3:43 a.m.
Created at: April 10, 2026, 4:49 a.m.