Triple

T10490607
Position Surface form Disambiguated ID Type / Status
Subject Kalenjin languages E247407 entity
Predicate hasMember P10 FINISHED
Object Terik language E866841 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: Terik language | Statement: [Kalenjin languages, hasMember, Terik language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terik language
Context triple: [Kalenjin languages, hasMember, Terik language]
  • A. Terik language chosen
    The Terik language is a Southern Nilotic language spoken by the Terik people of western Kenya, closely associated with neighboring Kalenjin groups such as the Kipsigis.
  • B. Temiar language
    The Temiar language is an Austroasiatic Aslian language spoken by the Temiar people of Peninsular Malaysia, known for its complex phonology and rich oral tradition.
  • C. Kaera language
    The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
  • D. Tikar language
    The Tikar language is a Bantoid language spoken primarily by the Tikar people of central Cameroon.
  • E. Teke-Kega language
    The Teke-Kega language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo and surrounding regions.
  • 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_69d94b0d05a88190be036a6e4ab374a7 completed April 10, 2026, 7:10 p.m.
Created at: April 6, 2026, 12:23 p.m.