Triple

T12022853
Position Surface form Disambiguated ID Type / Status
Subject Ajayi Crowther University E286197 entity
Predicate locatedIn P40 FINISHED
Object Oyo State E62860 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: Oyo State | Statement: [Ajayi Crowther University, locatedIn, Oyo State]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oyo State
Context triple: [Ajayi Crowther University, locatedIn, Oyo State]
  • A. Oyo State chosen
    Oyo State is a southwestern Nigerian state historically known as the heartland of the old Oyo Empire and a major center of Yoruba culture and politics.
  • 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. Ogun State
    Ogun State is a southwestern Nigerian state known as a key Yoruba cultural heartland and an important industrial and educational hub.
  • D. 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.
  • 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 (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_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903ee4f9081909e5a58ecbd830b14 completed April 10, 2026, 2:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd466577508190b1926c475b7c49dc completed May 8, 2026, 2:11 a.m.
Created at: April 8, 2026, 9:47 p.m.