Triple

T15195190
Position Surface form Disambiguated ID Type / Status
Subject Ali Farka Touré E363120 entity
Predicate placeOfDeath P21 FINISHED
Object Bamako, Mali 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, Mali | Statement: [Ali Farka Touré, placeOfDeath, Bamako, Mali]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bamako, Mali
Context triple: [Ali Farka Touré, placeOfDeath, Bamako, Mali]
  • 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. Koulikoro
    Koulikoro is a town and region in southwestern Mali, situated along the Niger River and serving as an important administrative and transport hub.
  • D. Koudougou
    Koudougou is a major city in central Burkina Faso known as an important commercial and transportation hub.
  • E. Sikasso
    Sikasso is a major city in southern Mali known as an important agricultural and commercial center near the borders with Burkina Faso and Côte d'Ivoire.
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0067eb710819085211fd05d5fa5f0 completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa92b99c48190b76e1306cf32a568 completed May 9, 2026, 9:37 p.m.
Created at: April 10, 2026, 3:10 a.m.