Triple

T21210354
Position Surface form Disambiguated ID Type / Status
Subject St. Michael’s Cathedral, Kontagora E522701 entity
Predicate hasDiocese P2740 FINISHED
Object Kontagora 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: Kontagora | Statement: [St. Michael’s Cathedral, Kontagora, hasDiocese, Kontagora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kontagora
Context triple: [St. Michael’s Cathedral, Kontagora, hasDiocese, Kontagora]
  • A. Kontagora chosen
    Kontagora is a town in Niger State, central Nigeria, known as an administrative and commercial center in the region.
  • B. Koutiala
    Koutiala is a major city in southern Mali known as an important center for cotton production and agriculture.
  • C. Larimna
    Larimna was an ancient Greek city of Opuntian Locris, situated on the coast of central Greece.
  • D. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • E. Bourkika
    Bourkika is a town and commune in northern Algeria, situated within the coastal Tipaza Province west of Algiers.
  • 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_69e0b5112d8881909510b2dcdc93106d completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73437b040819083d0070bd9c4e44b completed April 21, 2026, 8:24 a.m.
Created at: April 16, 2026, 3:35 p.m.