Triple

T13558781
Position Surface form Disambiguated ID Type / Status
Subject Ota E323849 entity
Predicate locatedIn P40 FINISHED
Object Ogun State 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: Ogun State | Statement: [Ota, locatedIn, Ogun State]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ogun State
Context triple: [Ota, locatedIn, Ogun State]
  • A. Ogun State chosen
    Ogun State is a southwestern Nigerian state known as a key Yoruba cultural heartland and an important industrial and educational hub.
  • B. Osun State
    Osun State is a southwestern Nigerian state that is a cultural and historical heartland of the Yoruba people, known for its traditional festivals and religious heritage.
  • C. Ondo State
    Ondo State is a coastal state in southwestern Nigeria known for its oil-producing areas, diverse ethnic communities, and significant role within the Niger Delta region.
  • D. Edo State
    Edo State is an inland state in southern Nigeria known for its capital Benin City, rich Benin Kingdom heritage, and role as a cultural and economic hub in the region.
  • E. Ekiti State
    Ekiti State is a landlocked, predominantly Yoruba-speaking state in southwestern Nigeria known for its hilly terrain and strong emphasis on education.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaff4223c8190801d153ae8f94c73 completed April 12, 2026, 2:45 p.m.
Created at: April 9, 2026, 9:47 p.m.