Triple

T4120134
Position Surface form Disambiguated ID Type / Status
Subject US Ouakam E92590 entity
Predicate city P40 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: [US Ouakam, city, Dakar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dakar
Context triple: [US Ouakam, city, 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. Saint-Louis, Senegal
    Saint-Louis, Senegal is a historic coastal city and former colonial capital of French West Africa, known for its distinctive island setting, colonial architecture, and cultural significance at the mouth of the Senegal River.
  • C. Nouakchott
    Nouakchott is the capital and largest city of Mauritania, located on the Atlantic coast of Northwest Africa.
  • D. Bamako
    Bamako is the capital and largest city of Mali, serving as a major political, economic, and cultural center in West Africa.
  • E. Port of Dakar
    The Port of Dakar is a major West African seaport and maritime hub in Senegal, serving as a key gateway for regional trade and shipping.
  • 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_69aed9685f70819086932777aec8d959 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69af0203b8c88190b08dd64800a37168 completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd678c2c088190a67867248f89c46a completed March 20, 2026, 3:28 p.m.
Created at: March 9, 2026, 3:41 p.m.