Triple

T23348702
Position Surface form Disambiguated ID Type / Status
Subject Duala (Cameroon) E591942 entity
Predicate closelyRelatedTo P37 FINISHED
Object Wumboko language
The Wumboko language is a Bantu language of Cameroon spoken by the Wumboko people in the coastal region near Douala.
 E1582042 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: Wumboko language | Statement: [Duala (Cameroon), closelyRelatedTo, Wumboko language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wumboko language
Context triple: [Duala (Cameroon), closelyRelatedTo, Wumboko language]
  • A. Kumbewaha language
    The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
  • B. Tembe language
    The Tembe language is an indigenous Tupi-Guarani language spoken by the Tembé people of northern Brazil.
  • C. Warumungu language
    The Warumungu language is an Australian Aboriginal language traditionally spoken by the Warumungu people of the Northern Territory, particularly around the Tennant Creek region.
  • D. Ngomba language
    Ngomba is a Bamileke language spoken in western Cameroon, belonging to the Grassfields branch of the Southern Bantoid languages.
  • E. Konongo language
    The Konongo language is a Bantu language of East Africa, closely related to Sukuma and spoken by the Konongo people.
  • 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: Wumboko language
Triple: [Duala (Cameroon), closelyRelatedTo, Wumboko language]
Generated description
The Wumboko language is a Bantu language of Cameroon spoken by the Wumboko people in the coastal region near Douala.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wumboko language
Target entity description: The Wumboko language is a Bantu language of Cameroon spoken by the Wumboko people in the coastal region near Douala.
  • A. Kumbewaha language
    The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
  • B. Tembe language
    The Tembe language is an indigenous Tupi-Guarani language spoken by the Tembé people of northern Brazil.
  • C. Warumungu language
    The Warumungu language is an Australian Aboriginal language traditionally spoken by the Warumungu people of the Northern Territory, particularly around the Tennant Creek region.
  • D. Ngomba language
    Ngomba is a Bamileke language spoken in western Cameroon, belonging to the Grassfields branch of the Southern Bantoid languages.
  • E. Konongo language
    The Konongo language is a Bantu language of East Africa, closely related to Sukuma and spoken by the Konongo people.
  • 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_69e25d20e3d08190bcede87673cafb25 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f199cb2a3c8190a5c0c8d8735256c7 completed April 29, 2026, 5:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c4cba927481908194b998075d522d completed May 19, 2026, 11:42 a.m.
NEDg Description generation batch_6a0c52f9ecc48190a8d5ae67566ea6ed completed May 19, 2026, 12:09 p.m.
NED2 Entity disambiguation (via description) batch_6a0c536bb21481908524a8ffe3084ebb completed May 19, 2026, 12:11 p.m.
Created at: April 17, 2026, 5:19 p.m.