Triple

T1128840
Position Surface form Disambiguated ID Type / Status
Subject Cameroon E24780 entity
Predicate majorCity P316 FINISHED
Object Bamenda
Bamenda is a prominent city in northwestern Cameroon known as a cultural and commercial hub of the Anglophone region.
 E136120 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: Bamenda | Statement: [Cameroon, majorCity, Bamenda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bamenda
Context triple: [Cameroon, majorCity, Bamenda]
  • A. Yaoundé
    Yaoundé is the political and administrative center of Cameroon, known for its hilly terrain and role as a major cultural and economic hub in Central Africa.
  • B. Malabo
    Malabo is the largest city and main economic and administrative center of Equatorial Guinea, located on the northern coast of Bioko Island in the Gulf of Guinea.
  • C. Luanda
    Luanda is the capital and largest city of Angola, a major Atlantic port and economic hub with a history shaped by Portuguese colonial rule and the transatlantic slave trade.
  • D. Douala
    Douala is the economic capital and main port city of Cameroon, located on the Wouri River along the Atlantic coast.
  • E. Libreville
    Libreville is the largest city and main economic and cultural center of Gabon, located on the country’s Atlantic coast.
  • 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: Bamenda
Triple: [Cameroon, majorCity, Bamenda]
Generated description
Bamenda is a prominent city in northwestern Cameroon known as a cultural and commercial hub of the Anglophone region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bamenda
Target entity description: Bamenda is a prominent city in northwestern Cameroon known as a cultural and commercial hub of the Anglophone region.
  • A. Yaoundé
    Yaoundé is the political and administrative center of Cameroon, known for its hilly terrain and role as a major cultural and economic hub in Central Africa.
  • B. Malabo
    Malabo is the largest city and main economic and administrative center of Equatorial Guinea, located on the northern coast of Bioko Island in the Gulf of Guinea.
  • C. Luanda
    Luanda is the capital and largest city of Angola, a major Atlantic port and economic hub with a history shaped by Portuguese colonial rule and the transatlantic slave trade.
  • D. Douala
    Douala is the economic capital and main port city of Cameroon, located on the Wouri River along the Atlantic coast.
  • E. Libreville
    Libreville is the largest city and main economic and cultural center of Gabon, located on the country’s Atlantic coast.
  • 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbdea9b88190a88da718bf5c1897 completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac763d917881908b3981a95d901717 completed March 7, 2026, 7:02 p.m.
NEDg Description generation batch_69ac76cf3c34819082dcbe772db7c46b completed March 7, 2026, 7:04 p.m.
NED2 Entity disambiguation (via description) batch_69ac77670fa08190827ef34ba9d52a70 completed March 7, 2026, 7:07 p.m.
Created at: March 1, 2026, 7:44 p.m.