Triple

T5410015
Position Surface form Disambiguated ID Type / Status
Subject First Ivorian Civil War E120990 entity
Predicate regionAffected P1586 FINISHED
Object Bouaké E256394 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: Bouaké | Statement: [First Ivorian Civil War, regionAffected, Bouaké]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bouaké
Context triple: [First Ivorian Civil War, regionAffected, Bouaké]
  • A. Bouaké chosen
    Bouaké is a major inland city in central Côte d'Ivoire known as an important commercial and transportation hub.
  • B. Yamoussoukro
    Yamoussoukro is the political capital of Côte d'Ivoire, known for its grand basilica and role as an administrative center in the French-speaking world.
  • C. Ouaga
    Ouaga is the commonly used short name for Ouagadougou, the capital and largest city of Burkina Faso.
  • D. 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.
  • E. Pointe-Noire
    Pointe-Noire is a major port city on the Atlantic coast of the Republic of the Congo and one of the country’s principal economic and industrial centers.
  • 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_69bd463a41cc8190b32ff5af2b96ca93 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd8796a420819092c1771407cd1a5d completed March 20, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf411f8f3c81908ca8578a388261c6 completed March 22, 2026, 1:08 a.m.
Created at: March 20, 2026, 2:05 p.m.