Triple

T5485622
Position Surface form Disambiguated ID Type / Status
Subject Diocese of Kontagora E123573 entity
Predicate cathedralLocatedIn P16620 FINISHED
Object Kontagora E522699 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: Kontagora | Statement: [Diocese of Kontagora, cathedralLocatedIn, Kontagora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kontagora
Context triple: [Diocese of Kontagora, cathedralLocatedIn, 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. 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.
  • D. Kaloum
    Kaloum is the central urban commune of Conakry, Guinea, encompassing the city’s historic core, main government institutions, and port area.
  • E. Kondura
    Kondura is an Indian film directed by acclaimed filmmaker Shyam Benegal, known for its exploration of social and moral themes within a rural setting.
  • 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_69bd4648883481909e9775d43300c5fa completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd92625a50819088133641ed6f25a9 completed March 20, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf6c812d4c8190a22f76b787ab0f10 completed March 22, 2026, 4:13 a.m.
Created at: March 20, 2026, 2:10 p.m.