Triple

T10490433
Position Surface form Disambiguated ID Type / Status
Subject Kunama languages E247402 entity
Predicate hasMember P10 FINISHED
Object Barka Kunama E476910 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: Barka Kunama | Statement: [Kunama languages, hasMember, Barka Kunama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barka Kunama
Context triple: [Kunama languages, hasMember, Barka Kunama]
  • A. Barka Kunama chosen
    Barka Kunama is a dialect of the Kunama language spoken by Kunama communities, primarily in parts of Eritrea and neighboring regions.
  • B. Gardabani
    Gardabani is a town in southeastern Georgia known for its role as an industrial and energy hub within the Kvemo Kartli region.
  • C. Zabdeno
    Zabdeno is a viral vector vaccine that uses a human adenovirus serotype 26 platform to provide protection against Ebola virus disease.
  • D. Borama
    Borama is a city in northwestern Somalia’s Awdal region, known as a cultural and educational center for the Somali people.
  • E. Nyishi
    The Nyishi are one of the major indigenous tribes of northeastern India, known for their distinct language, traditional bamboo and cane craftsmanship, and rich cultural heritage.
  • 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_69d933c5caa08190a5fba92ebf4b0ff9 completed April 10, 2026, 5:30 p.m.
Created at: April 6, 2026, 12:23 p.m.