Triple

T21917137
Position Surface form Disambiguated ID Type / Status
Subject Bamileke languages E541208 entity
Predicate hasMember P10 FINISHED
Object Ngomba language
Ngomba is a Bamileke language spoken in western Cameroon, belonging to the Grassfields branch of the Southern Bantoid languages.
 E1508086 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: Ngomba language | Statement: [Bamileke languages, hasMember, Ngomba language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ngomba language
Context triple: [Bamileke languages, hasMember, Ngomba language]
  • A. Nyemba language
    The Nyemba language is a Bantu language spoken primarily by the Nyemba (Nyaneka-Nkhumbi) people of southwestern Angola.
  • B. Tembe language
    The Tembe language is an indigenous Tupi-Guarani language spoken by the Tembé people of northern Brazil.
  • C. Ngamo language
    The Ngamo language is a West Chadic language spoken primarily in northeastern Nigeria by the Ngamo people.
  • D. Nsenga language
    The Nsenga language is a Bantu language spoken primarily in Zambia and neighboring regions, closely related to other languages of the area such as Tumbuka and Chewa.
  • E. Azande language
    Azande language is a Ubangian language spoken primarily by the Azande people across parts of South Sudan, the Central African Republic, and the Democratic Republic of the Congo.
  • 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: Ngomba language
Triple: [Bamileke languages, hasMember, Ngomba language]
Generated description
Ngomba is a Bamileke language spoken in western Cameroon, belonging to the Grassfields branch of the Southern Bantoid languages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ngomba language
Target entity description: Ngomba is a Bamileke language spoken in western Cameroon, belonging to the Grassfields branch of the Southern Bantoid languages.
  • A. Nyemba language
    The Nyemba language is a Bantu language spoken primarily by the Nyemba (Nyaneka-Nkhumbi) people of southwestern Angola.
  • B. Tembe language
    The Tembe language is an indigenous Tupi-Guarani language spoken by the Tembé people of northern Brazil.
  • C. Ngamo language
    The Ngamo language is a West Chadic language spoken primarily in northeastern Nigeria by the Ngamo people.
  • D. Nsenga language
    The Nsenga language is a Bantu language spoken primarily in Zambia and neighboring regions, closely related to other languages of the area such as Tumbuka and Chewa.
  • E. Azande language
    Azande language is a Ubangian language spoken primarily by the Azande people across parts of South Sudan, the Central African Republic, and the Democratic Republic of the Congo.
  • 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_69e0c47c4b9c8190a5586a75f5f36453 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1233858308190a877d8015db4d380 completed April 28, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a5a13f09c819088b50585423a1835 completed May 18, 2026, 12:15 a.m.
NEDg Description generation batch_6a0a5a967d28819084a37207e17d4f68 completed May 18, 2026, 12:17 a.m.
NED2 Entity disambiguation (via description) batch_6a0a5b24f6708190bfe903dceb0e9210 completed May 18, 2026, 12:19 a.m.
Created at: April 16, 2026, 7:43 p.m.