Triple

T10490604
Position Surface form Disambiguated ID Type / Status
Subject Kalenjin languages E247407 entity
Predicate hasMember P10 FINISHED
Object Marakwet language E866840 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: Marakwet language | Statement: [Kalenjin languages, hasMember, Marakwet language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marakwet language
Context triple: [Kalenjin languages, hasMember, Marakwet language]
  • A. Marakwet language chosen
    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.
  • B. Malasanga language
    The Malasanga language is an Oceanic language spoken in Papua New Guinea, belonging to the Kula–Malasanga subgroup of the Austronesian language family.
  • C. Murle language
    The Murle language is an Eastern Sudanic language spoken primarily by the Murle people of South Sudan.
  • D. Sanglechi language
    The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
  • E. Ngada language
    The Ngada language is an Austronesian language spoken by the Ngada people in central Flores, Indonesia, known for its complex verbal morphology and rich oral tradition.
  • 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.