Triple

T6077252
Position Surface form Disambiguated ID Type / Status
Subject West Region E135430 entity
Predicate hasMajorCity P316 FINISHED
Object Mbouda
Mbouda is a significant urban center in western Cameroon known for its role as a commercial and administrative hub in the region.
E569435 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: Mbouda | Statement: [West Region, hasMajorCity, Mbouda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mbouda
Context triple: [West Region, hasMajorCity, Mbouda]
  • A. Maroua
    Maroua is a prominent city in northern Cameroon known as a regional commercial and cultural center near the Sahel.
  • B. Benina
    Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
  • C. Eyamba
    Eyamba is a prominent clan of the Efik people of southeastern Nigeria, historically associated with leadership and influence in the Old Calabar region.
  • D. Ubangi-Shari
    Ubangi-Shari was the French colonial territory in central Africa that later became the independent nation of the Central African Republic.
  • E. Ebanga
    Ebanga is a monoclonal antibody drug used to treat Zaire ebolavirus infection (Ebola virus disease).
  • 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: Mbouda
Triple: [West Region, hasMajorCity, Mbouda]
Generated description
Mbouda is a significant urban center in western Cameroon known for its role as a commercial and administrative hub in the region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mbouda
Target entity description: Mbouda is a significant urban center in western Cameroon known for its role as a commercial and administrative hub in the region.
  • A. Maroua
    Maroua is a prominent city in northern Cameroon known as a regional commercial and cultural center near the Sahel.
  • B. Benina
    Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
  • C. Eyamba
    Eyamba is a prominent clan of the Efik people of southeastern Nigeria, historically associated with leadership and influence in the Old Calabar region.
  • D. Ubangi-Shari
    Ubangi-Shari was the French colonial territory in central Africa that later became the independent nation of the Central African Republic.
  • E. Ebanga
    Ebanga is a monoclonal antibody drug used to treat Zaire ebolavirus infection (Ebola virus disease).
  • 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_69c0087ad31c8190ab936e0ff28614b6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0576ef2c88190b0ec62e9f041d176 completed March 22, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1252a178c81909a3d689ad748fb5e completed March 23, 2026, 11:34 a.m.
NEDg Description generation batch_69c1288420dc8190bd70eba4c1a789df completed March 23, 2026, 11:48 a.m.
NED2 Entity disambiguation (via description) batch_69c129259d988190aa53f1637ff05be5 completed March 23, 2026, 11:51 a.m.
Created at: March 22, 2026, 4:11 p.m.