Triple

T11303671
Position Surface form Disambiguated ID Type / Status
Subject Gikuyu E267659 entity
Predicate alternateName P39 FINISHED
Object Kikuyu E53602 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: Kikuyu | Statement: [Gikuyu, alternateName, Kikuyu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kikuyu
Context triple: [Gikuyu, alternateName, Kikuyu]
  • A. Kikuyu chosen
    Kikuyu is a major Bantu language spoken primarily by the Kikuyu people of central Kenya.
  • B. Kikuyu
    Kikuyu is a town in Kenya’s Nairobi Metropolitan Region, known as a fast-growing residential and commercial center west of Nairobi.
  • C. Coolabah
    Coolabah is a small rural town in western New South Wales, Australia, known for its remote outback setting and role as a service stop along regional transport routes.
  • D. Murrurundi
    Murrurundi is a small rural town in New South Wales, Australia, known for its scenic setting in the Upper Hunter region and its historic buildings.
  • E. Kikuyu highlands
    The Kikuyu highlands are a fertile, densely populated upland region in central Kenya, historically inhabited by the Kikuyu people and known for its agriculture and proximity to Nairobi.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9a5c3788190ba54eda514b97903 completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e50a57366081908a05fc52c5d4074c completed April 19, 2026, 5:01 p.m.
Created at: April 8, 2026, 9:32 p.m.