Triple

T8499147
Position Surface form Disambiguated ID Type / Status
Subject Modibo Keita International Airport E201171 entity
Predicate servesCity P82 FINISHED
Object Bamako E69241 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: Bamako | Statement: [Modibo Keita International Airport, servesCity, Bamako]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bamako
Context triple: [Modibo Keita International Airport, servesCity, Bamako]
  • A. Bamako chosen
    Bamako is the capital and largest city of Mali, serving as a major political, economic, and cultural center in West Africa.
  • B. Ouagadougou
    Ouagadougou is the capital and largest city of Burkina Faso, serving as its political, economic, and cultural center in the Sahel region.
  • C. 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.
  • D. Koudougou
    Koudougou is a major city in central Burkina Faso known as an important commercial and transportation hub.
  • E. Niamey
    Niamey is the capital and largest city of Niger, situated along the Niger River and serving as the country’s political, economic, and cultural center.
  • 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_69ca831ee390819095fae73400bbfafc completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5984d7481908c41c57bef9cf254 completed March 31, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8411e148190a700dae3d3ebd716 completed April 2, 2026, 5:32 p.m.
Created at: March 30, 2026, 6:14 p.m.