Triple

T4231572
Position Surface form Disambiguated ID Type / Status
Subject Saint-Louis E94591 entity
Predicate capitalOf P204 FINISHED
Object Saint-Louis Department E363162 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: Saint-Louis Department | Statement: [Saint-Louis, capitalOf, Saint-Louis Department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saint-Louis Department
Context triple: [Saint-Louis, capitalOf, Saint-Louis Department]
  • A. Saint-Louis Department chosen
    Saint-Louis Department is an administrative division in northern Senegal that encompasses the historic city of Saint-Louis and its surrounding areas.
  • B. Ouest Department
    Ouest Department is an administrative region in western Haiti that includes the capital city, Port-au-Prince, and serves as the country’s political and economic center.
  • C. Dakar Department
    Dakar Department is an administrative division in western Senegal that encompasses the nation’s capital city and serves as its primary political and economic hub.
  • D. Beni Department
    Beni Department is a large, sparsely populated administrative region in northern Bolivia known for its vast Amazonian lowlands, wetlands, and cattle ranching.
  • E. Sud Department
    Sud Department is an administrative region in southern Haiti known for its coastal cities, beaches, and agricultural activities.
  • 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_69b34537cc6481909cd0a96acbb33ef7 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e642aac8190977dd101e27afcbb completed March 12, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b77632d08190ab7c12986e2cee61 completed March 14, 2026, 7:31 p.m.
Created at: March 12, 2026, 11:05 p.m.