Triple

T12381500
Position Surface form Disambiguated ID Type / Status
Subject Africa Sports d’Abidjan E295755 entity
Predicate location P40 FINISHED
Object Abidjan E67982 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: Abidjan | Statement: [Africa Sports d’Abidjan, location, Abidjan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abidjan
Context triple: [Africa Sports d’Abidjan, location, Abidjan]
  • A. Abidjan chosen
    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.
  • B. Cotonou
    Cotonou is the largest city and economic hub of Benin, located on the Gulf of Guinea in West Africa.
  • 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. Bamako
    Bamako is the capital and largest city of Mali, serving as a major political, economic, and cultural center in West Africa.
  • E. Libreville
    Libreville is the largest city and main economic and cultural center of Gabon, located on the country’s Atlantic coast.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fbb3a2481908c2fcb5e6488eb3c completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ac5b46c81908d419e09f5629c37 completed May 2, 2026, 4:48 p.m.
Created at: April 8, 2026, 9:54 p.m.