Triple

T16596364
Position Surface form Disambiguated ID Type / Status
Subject Malian Air Force E403216 entity
Predicate headquartersLocation P62 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: [Malian Air Force, headquartersLocation, Bamako]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bamako
Context triple: [Malian Air Force, headquartersLocation, 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_69d883880d0c81908b5fcd454e767b60 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35d723c508190b5afbda5eec5abea completed April 18, 2026, 10:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00918ae5f48190a85af2dfbe9708d4 completed May 10, 2026, 2:09 p.m.
Created at: April 10, 2026, 5:16 a.m.