Triple

T10582164
Position Surface form Disambiguated ID Type / Status
Subject Munukutuba E249762 entity
Predicate alternateName P39 FINISHED
Object Kituba E51306 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: Kituba | Statement: [Munukutuba, alternateName, Kituba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kituba
Context triple: [Munukutuba, alternateName, Kituba]
  • A. Kituba chosen
    Kituba is a widely spoken Bantu-based creole language of Central Africa, serving as a major lingua franca in the Republic of the Congo and surrounding regions.
  • B. Kwanyama
    Kwanyama is a major standardized dialect of the Ovambo language spoken primarily in northern Namibia and southern Angola.
  • C. Kikongo
    Kikongo is a Bantu language widely spoken in Central Africa, particularly in the western regions of the Democratic Republic of the Congo and neighboring countries.
  • D. Kichwa
    Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
  • E. Kimbundu
    Kimbundu is a major Bantu language spoken primarily in northwestern Angola, especially around the capital Luanda, by the Ambundu people.
  • 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_69d381c9d3d48190a29ee491e1696a0e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d52766d53c8190b51753768ab58c31 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b78ff28819085acf84418d54733 completed April 10, 2026, 7:11 p.m.
Created at: April 6, 2026, 12:39 p.m.