Triple

T10490603
Position Surface form Disambiguated ID Type / Status
Subject Kalenjin languages E247407 entity
Predicate hasMember P10 FINISHED
Object Keiyo language E865566 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: Keiyo language | Statement: [Kalenjin languages, hasMember, Keiyo language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keiyo language
Context triple: [Kalenjin languages, hasMember, Keiyo language]
  • A. Keiyo language chosen
    The Keiyo language is a Southern Nilotic language spoken by the Keiyo people of Kenya’s Rift Valley, closely associated with and linguistically similar to other Kalenjin languages such as Kipsigis.
  • B. Kei language
    Kei language is an Austronesian language spoken primarily on the Kei (Kai) Islands in southeastern Maluku, Indonesia.
  • C. Kawaiisu language
    Kawaiisu language is an endangered Uto-Aztecan language traditionally spoken by the Kawaiisu people of southern California.
  • D. Kiga language
    The Kiga language is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda.
  • E. Miyako language
    The Miyako language is a Southern Ryukyuan language of Japan’s Okinawa Prefecture, spoken primarily on the Miyako Islands and noted for its distinct phonology and endangered status.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5097d61e08190952d4354ef1bce52 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95e5d1a2c81908a9bb8f1c55414fa completed April 10, 2026, 8:32 p.m.
Created at: April 6, 2026, 12:23 p.m.