Triple

T20062239
Position Surface form Disambiguated ID Type / Status
Subject Maritime Region E499506 entity
Predicate hasMajorCity P316 FINISHED
Object Lomé 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: Lomé | Statement: [Maritime Region, hasMajorCity, Lomé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lomé
Context triple: [Maritime Region, hasMajorCity, Lomé]
  • A. Lomé chosen
    Lomé is the coastal capital and largest city of Togo, serving as a key economic and cultural hub 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. 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. Abomey-Calavi
    Abomey-Calavi is a major city in southern Benin, functioning as a rapidly growing suburban and academic hub near the economic capital Cotonou.
  • E. Abidji
    Abidji is a Kwa language of the Central Tano subgroup spoken by the Abidji people in southern Côte d’Ivoire.
  • 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66376f2d4819081b9e1b265650e5b completed April 20, 2026, 5:33 p.m.
Created at: April 11, 2026, 3:39 p.m.