Triple

T2712408
Position Surface form Disambiguated ID Type / Status
Subject Bight of Benin E59892 entity
Predicate hasCoastalCity P969 FINISHED
Object Lomé E71688 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: Lomé | Statement: [Bight of Benin, hasCoastalCity, Lomé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lomé
Context triple: [Bight of Benin, hasCoastalCity, 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. 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.
  • 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_69ab4ac92a088190bc74bca14038e3de completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda90d5a88190bcb6caefd8f2dd1b completed March 7, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb68552848190ad2e615e16716fa1 completed March 10, 2026, 6:13 a.m.
Created at: March 6, 2026, 9:55 p.m.