Triple

T540179
Position Surface form Disambiguated ID Type / Status
Subject West Africa E12611 entity
Predicate hasMajorCity P316 FINISHED
Object Dakar E13945 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: Dakar | Statement: [West Africa, hasMajorCity, Dakar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dakar
Context triple: [West Africa, hasMajorCity, Dakar]
  • A. Dakar chosen
    Dakar is the capital and largest city of Senegal, located on the Atlantic coast and serving as a major political, economic, and cultural hub of West Africa.
  • B. Nouakchott
    Nouakchott is the capital and largest city of Mauritania, located on the Atlantic coast of Northwest Africa.
  • C. Abidjan
    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.
  • D. Libreville
    Libreville is the largest city and main economic and cultural center of Gabon, located on the country’s Atlantic coast.
  • E. Tadjoura
    Tadjoura is a historic coastal town in Djibouti on the Gulf of Tadjoura, known as one of the country’s oldest settlements and a traditional trading hub.
  • 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_69a49334226c81908b0ea1689ef6aa3f completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4985feee481908184a39210feab95 completed March 1, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4e02ab7dc819092a210eb0fcd59f4 completed March 2, 2026, 12:56 a.m.
Created at: March 1, 2026, 7:32 p.m.