Triple

T12409159
Position Surface form Disambiguated ID Type / Status
Subject Northwest Bantu E296467 entity
Predicate hasMemberLanguage P7390 FINISHED
Object Ngumba language
Ngumba language is a Bantu language spoken primarily in Cameroon by the Ngumba people.
 E982522 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: Ngumba language | Statement: [Northwest Bantu, hasMemberLanguage, Ngumba language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ngumba language
Context triple: [Northwest Bantu, hasMemberLanguage, Ngumba language]
  • A. Medumba language
    Medumba is a Bantu-related Grassfields language spoken primarily by the Bamileke people in western Cameroon.
  • B. Nyunga language
    The Nyunga language is an Australian Aboriginal language traditionally spoken by the Noongar people of southwestern Western Australia and is part of the broader Pama–Nyungan language family.
  • C. Kumbewaha language
    The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
  • D. Lumbu language
    Lumbu language is a Bantu language spoken by the Lumbu people, primarily in parts of Gabon and the Republic of the Congo.
  • E. Gbaya-Mbodomo language
    The Gbaya-Mbodomo language is a Niger-Congo language spoken by the Gbaya people of Central Africa, particularly in parts of the Central African Republic and neighboring regions.
  • 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: Ngumba language
Triple: [Northwest Bantu, hasMemberLanguage, Ngumba language]
Generated description
Ngumba language is a Bantu language spoken primarily in Cameroon by the Ngumba people.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ngumba language
Target entity description: Ngumba language is a Bantu language spoken primarily in Cameroon by the Ngumba people.
  • A. Medumba language
    Medumba is a Bantu-related Grassfields language spoken primarily by the Bamileke people in western Cameroon.
  • B. Nyunga language
    The Nyunga language is an Australian Aboriginal language traditionally spoken by the Noongar people of southwestern Western Australia and is part of the broader Pama–Nyungan language family.
  • C. Kumbewaha language
    The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
  • D. Lumbu language
    Lumbu language is a Bantu language spoken by the Lumbu people, primarily in parts of Gabon and the Republic of the Congo.
  • E. Gbaya-Mbodomo language
    The Gbaya-Mbodomo language is a Niger-Congo language spoken by the Gbaya people of Central Africa, particularly in parts of the Central African Republic and neighboring regions.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d4b86c88190afba0de15b34eee9 completed April 10, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6348af5a8819083a075d145b15fd4 completed May 2, 2026, 5:29 p.m.
NEDg Description generation batch_69f638cbb6dc8190a80ffe3430337855 completed May 2, 2026, 5:47 p.m.
NED2 Entity disambiguation (via description) batch_69f6397a3458819095b94ae7f9d5f106 completed May 2, 2026, 5:50 p.m.
Created at: April 8, 2026, 9:55 p.m.