Triple

T10490411
Position Surface form Disambiguated ID Type / Status
Subject Maasai E247401 entity
Predicate closelyRelatedTo P37 FINISHED
Object Samburu language E50220 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: Samburu language | Statement: [Maasai, closelyRelatedTo, Samburu language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samburu language
Context triple: [Maasai, closelyRelatedTo, Samburu language]
  • A. Mamboru language
    The Mamboru language is an Austronesian language spoken by a small community on Sumba Island in eastern Indonesia.
  • B. Maasai language chosen
    Maasai language is an Eastern Nilotic language spoken primarily by the Maasai people of Kenya and Tanzania, known for its rich oral tradition and distinctive phonology.
  • C. Turkana language
    The Turkana language is an Eastern Nilotic language spoken primarily by the Turkana people of northwestern Kenya.
  • D. Kipsigis language
    The Kipsigis language is a Southern Nilotic language spoken by the Kipsigis people of Kenya, forming part of the broader Kalenjin language cluster.
  • E. Nyaturu language
    The Nyaturu language is a Bantu language spoken primarily by the Nyaturu people in central Tanzania.
  • 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_69d8dc9792308190b09d6aaed63dd418 completed April 10, 2026, 11:18 a.m.
Created at: April 6, 2026, 12:23 p.m.