Triple

T14998675
Position Surface form Disambiguated ID Type / Status
Subject Kajiado County E374024 entity
Predicate languageSpoken P151 FINISHED
Object Maasai 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: Maasai language | Statement: [Kajiado County, languageSpoken, Maasai language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maasai language
Context triple: [Kajiado County, languageSpoken, Maasai language]
  • A. 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.
  • B. Marakwet language
    The Marakwet language is a Southern Nilotic language spoken by the Marakwet people of Kenya and is closely related to other Kalenjin languages such as Kipsigis.
  • C. Mamboru language
    The Mamboru language is an Austronesian language spoken by a small community on Sumba Island in eastern Indonesia.
  • D. Turkana language
    The Turkana language is an Eastern Nilotic language spoken primarily by the Turkana people of northwestern Kenya.
  • E. 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.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded71a5618819083ae96a79735ef98 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe969c3ba88190899f06b185e94ccf completed May 9, 2026, 2:06 a.m.
Created at: April 10, 2026, 2:54 a.m.