Triple

T22524151
Position Surface form Disambiguated ID Type / Status
Subject Niamey Convention E556856 entity
Predicate signedInCity P4488 FINISHED
Object Niamey 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: Niamey | Statement: [Niamey Convention, signedInCity, Niamey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niamey
Context triple: [Niamey Convention, signedInCity, 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. Niamey Zarma
    Niamey Zarma is the principal urban dialect of the Zarma language, predominantly spoken in and around Niger’s capital city, Niamey.
  • C. Bamako
    Bamako is the capital and largest city of Mali, serving as a major political, economic, and cultural center in West Africa.
  • D. 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.
  • E. Ouagadougou
    Ouagadougou is the capital and largest city of Burkina Faso, serving as its political, economic, and cultural center in the Sahel region.
  • 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_69e11e5657e881909f16ca58352c50da completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15e34590c81909e4ed1c95f13a199 completed April 29, 2026, 1:26 a.m.
Created at: April 16, 2026, 8:51 p.m.