Triple

T12602947
Position Surface form Disambiguated ID Type / Status
Subject Luba languages E300902 entity
Predicate ethnolinguisticGroup P3349 FINISHED
Object Luba E492319 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: Luba | Statement: [Luba languages, ethnolinguisticGroup, Luba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luba
Context triple: [Luba languages, ethnolinguisticGroup, Luba]
  • A. Luba
    Luba is a coastal town and important port on the southern part of Bioko Island in Equatorial Guinea.
  • B. Luba chosen
    The Luba are a major Bantu-speaking ethnic group of Central Africa, historically known for the powerful Luba Kingdom centered in what is now the Democratic Republic of the Congo.
  • C. Lunda
    Lunda is a Bantu language spoken primarily by the Lunda people in parts of Zambia, Angola, and the Democratic Republic of the Congo.
  • D. Lubemba
    Lubemba is the traditional kingdom and cultural heartland of the Bemba people in what is now northern Zambia.
  • E. Mbanza Kongo
    Mbanza Kongo is a historic city in northern Angola that served as the political and spiritual center of the precolonial Kingdom of Kongo and is now recognized as a UNESCO World Heritage Site.
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954e6e20481908bca684c4b497c48 completed April 10, 2026, 7:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ecb09e481909d688f174372dde7 completed May 2, 2026, 8:30 p.m.
Created at: April 9, 2026, 5:10 p.m.