Triple

T6435656
Position Surface form Disambiguated ID Type / Status
Subject Prime Minister of Cameroon E129887 entity
Predicate residence P75 FINISHED
Object Yaoundé E129885 NE FINISHED

How this triple was built (2 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: Yaoundé | Statement: [Prime Minister of Cameroon, residence, Yaoundé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yaoundé
Context triple: [Prime Minister of Cameroon, residence, Yaoundé]
  • A. Yaoundé chosen
    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. Douala
    Douala is the economic capital and main port city of Cameroon, located on the Wouri River along the Atlantic coast.
  • C. Ouaga
    Ouaga is the commonly used short name for Ouagadougou, the capital and largest city of Burkina Faso.
  • D. Libreville
    Libreville is the largest city and main economic and cultural center of Gabon, located on the country’s Atlantic coast.
  • E. Brazzaville
    Brazzaville is the capital and largest city of the Republic of the Congo, located on the Congo River directly across from Kinshasa in Central Africa.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c0084caac48190a7bc2ad8ba44536f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c069415c3c8190b91bd12ae79edd26 completed March 22, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6538ca31c8190b4a24662c4eeffe9 completed March 27, 2026, 9:53 a.m.
Created at: March 22, 2026, 4:45 p.m.