Triple

T2662945
Position Surface form Disambiguated ID Type / Status
Subject Lingala E54766 entity
Predicate hasDialects P4251 FINISHED
Object Standard Lingala E54766 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: Standard Lingala | Statement: [Lingala, hasDialects, Standard Lingala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Standard Lingala
Context triple: [Lingala, hasDialects, Standard Lingala]
  • A. Lingala chosen
    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.
  • B. 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.
  • 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. Ngbandi language
    The Ngbandi language is a Central Sudanic language spoken primarily in the Central African Republic and the Democratic Republic of the Congo, known for being the linguistic source of the trade language Sango.
  • 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_69ab49e028948190b97e01d73548b1d9 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd96b9f1c8190a8a9460ca88a9aaf completed March 7, 2026, 7:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98dc36d8819086fc739c324f0761 completed March 10, 2026, 4:06 a.m.
Created at: March 6, 2026, 9:53 p.m.