Triple

T1813141
Position Surface form Disambiguated ID Type / Status
Subject Mali E40373 entity
Predicate largestCity P235 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: [Mali, largestCity, Bamako]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bamako
Context triple: [Mali, largestCity, 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. 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.
  • E. Abidjan
    Abidjan is a major economic and cultural hub on the southern coast of Côte d'Ivoire, known for its bustling port, modern skyline, and status as one of the largest cities in West 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_69a88643a3388190a612f2ebe1fb29e7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa65c775408190b4f5912786720e28 completed March 6, 2026, 5:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69addf42de6081908182cd3bda9c69e9 completed March 8, 2026, 8:42 p.m.
Created at: March 4, 2026, 7:32 p.m.