Triple

T13363203
Position Surface form Disambiguated ID Type / Status
Subject Meru E318870 entity
Predicate roadConnection P385 FINISHED
Object Isiolo E1045966 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: Isiolo | Statement: [Meru, roadConnection, Isiolo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isiolo
Context triple: [Meru, roadConnection, Isiolo]
  • A. Isiolo chosen
    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.
  • B. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • C. Wazaramo
    Wazaramo are a Bantu-speaking ethnic group native to the coastal and near-coastal regions around Dar es Salaam in eastern Tanzania.
  • D. Nyamira
    Nyamira is a town in western Kenya that serves as an administrative and commercial center in the former Nyanza region.
  • E. Kisii
    Kisii is a bustling commercial and administrative town in southwestern Kenya, serving as a key hub for the surrounding agricultural highlands and the Kisii community.
  • 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_69d806b7bbac8190b85278c87fa7aff3 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69da628affd081909f1790d333f0eef4 completed April 11, 2026, 3:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76b9ec6848190b8e986d849756050 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:32 p.m.