Triple

T21644365
Position Surface form Disambiguated ID Type / Status
Subject Djenné E534176 entity
Predicate governingCountryCapital P204 FINISHED
Object Bamako NE NERFINISHED

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: [Djenné, governingCountryCapital, Bamako]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bamako
Context triple: [Djenné, governingCountryCapital, 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 (2 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_69e0c466aec88190ba39c7543dbc8ba2 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef5393ed388190a0bc385de2b861bf completed April 27, 2026, 12:16 p.m.
Created at: April 16, 2026, 6:35 p.m.