Triple

T1340587
Position Surface form Disambiguated ID Type / Status
Subject Jamaican Patois E28453 entity
Predicate influencedByLanguage P4183 FINISHED
Object Kikongo E57354 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: Kikongo | Statement: [Jamaican Patois, influencedByLanguage, Kikongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kikongo
Context triple: [Jamaican Patois, influencedByLanguage, Kikongo]
  • A. Kikongo chosen
    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.
  • B. Lingala
    Lingala is a Bantu language widely spoken as a lingua franca in the Democratic Republic of the Congo and the Republic of the Congo, especially in urban centers and along the Congo River.
  • C. Kimbundu
    Kimbundu is a major Bantu language spoken primarily in northwestern Angola, especially around the capital Luanda, by the Ambundu people.
  • D. Kirundi
    Kirundi is a Bantu language primarily spoken in Burundi and neighboring regions of East Africa.
  • E. Kituba
    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.
  • 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_69a49854eb3481908c7d56b2e449a290 completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c48e6534819090d23f3cc25093ae completed March 1, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc6305c988190830dd535726c6338 completed March 8, 2026, 12:43 a.m.
Created at: March 1, 2026, 7:56 p.m.