Triple

T1147050
Position Surface form Disambiguated ID Type / Status
Subject Francophonie E23588 entity
Predicate hasKeyCity P316 FINISHED
Object Niamey E72364 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: Niamey | Statement: [Francophonie, hasKeyCity, Niamey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niamey
Context triple: [Francophonie, hasKeyCity, Niamey]
  • A. Niamey chosen
    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.
  • B. Bamako
    Bamako is the capital and largest city of Mali, serving as a major political, economic, and cultural center in West Africa.
  • C. Ouagadougou
    Ouagadougou is the capital and largest city of Burkina Faso, serving as its political, economic, and cultural center in the Sahel region.
  • D. Yaoundé
    Yaoundé is the political and administrative center of Cameroon, known for its hilly terrain and role as a major cultural and economic hub in Central Africa.
  • E. N'Djamena
    N'Djamena is the largest city and political, economic, and cultural center of Chad, located in the southwestern part of the country near the border with Cameroon.
  • 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bf13ab648190931dea78202096e4 completed March 1, 2026, 10:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac99730c408190a705ca67a6724778 completed March 7, 2026, 9:32 p.m.
Created at: March 1, 2026, 7:44 p.m.