Triple

T7161883
Position Surface form Disambiguated ID Type / Status
Subject Central Bantu E166965 entity
Predicate hasMajorLanguage P207 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: [Central Bantu, hasMajorLanguage, Kituba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kituba
Context triple: [Central Bantu, hasMajorLanguage, 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_69c68887a5cc8190bec0ea96227164f7 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e82e4b248190ad3c3863cb93971e completed March 27, 2026, 8:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7adc4b7648190969fab0351f9fd22 completed March 28, 2026, 10:30 a.m.
Created at: March 27, 2026, 2:47 p.m.