Triple

T7544168
Position Surface form Disambiguated ID Type / Status
Subject Ubangian E178353 entity
Predicate majorLanguage P207 FINISHED
Object Ngbandi
Ngbandi is a Central African language spoken primarily in the Democratic Republic of the Congo and the Central African Republic, known for its role as a regional lingua franca and its inclusion in the Ubangian language family.
 E672799 NE FINISHED

How this triple was built (4 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: Ngbandi | Statement: [Ubangian, majorLanguage, Ngbandi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ngbandi
Context triple: [Ubangian, majorLanguage, Ngbandi]
  • A. Mbanderu
    Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
  • B. Banda-Yangere
    Banda-Yangere is a dialect of the Central Banda language spoken by Banda communities in parts of Central Africa.
  • C. Makouda
    Makouda is a town and commune located in northern Algeria within the Kabylie region.
  • D. Mbundu
    Mbundu is a major Bantu ethnic group of Angola, known for its distinct language and significant cultural and historical influence in the region.
  • E. Khondji
    Khondji is the surname of Darius Khondji, a renowned cinematographer known for his visually distinctive work on international films.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ngbandi
Triple: [Ubangian, majorLanguage, Ngbandi]
Generated description
Ngbandi is a Central African language spoken primarily in the Democratic Republic of the Congo and the Central African Republic, known for its role as a regional lingua franca and its inclusion in the Ubangian language family.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ngbandi
Target entity description: Ngbandi is a Central African language spoken primarily in the Democratic Republic of the Congo and the Central African Republic, known for its role as a regional lingua franca and its inclusion in the Ubangian language family.
  • A. Mbanderu
    Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
  • B. Banda-Yangere
    Banda-Yangere is a dialect of the Central Banda language spoken by Banda communities in parts of Central Africa.
  • C. Makouda
    Makouda is a town and commune located in northern Algeria within the Kabylie region.
  • D. Mbundu
    Mbundu is a major Bantu ethnic group of Angola, known for its distinct language and significant cultural and historical influence in the region.
  • E. Khondji
    Khondji is the surname of Darius Khondji, a renowned cinematographer known for his visually distinctive work on international films.
  • F. None of above. chosen

Provenance (5 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_69c69f2be3888190a6667a27f8f195e9 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f896a27481908b2e120208f268e7 completed March 27, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856b93188819080c769a2a1b122f4 completed March 28, 2026, 10:31 p.m.
NEDg Description generation batch_69c857738e6881908abfce108d71efc0 completed March 28, 2026, 10:34 p.m.
NED2 Entity disambiguation (via description) batch_69c857e4a0408190b395389c6221e259 completed March 28, 2026, 10:36 p.m.
Created at: March 27, 2026, 3:48 p.m.