Triple

T18575539
Position Surface form Disambiguated ID Type / Status
Subject Ituku-Ozalla campus E453976 entity
Predicate locatedNear P294 FINISHED
Object Enugu 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: Enugu | Statement: [Ituku-Ozalla campus, locatedNear, Enugu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Enugu
Context triple: [Ituku-Ozalla campus, locatedNear, Enugu]
  • A. Enugu chosen
    Enugu is a major city in southeastern Nigeria known historically for its coal mining industry and role as a regional administrative and economic center.
  • B. Owerri
    Owerri is the capital and largest city of Imo State in southeastern Nigeria, known as a regional cultural and commercial center.
  • C. Onitsha
    Onitsha is a major commercial and river port city on the eastern bank of the Niger River in southeastern Nigeria, known for its large open-air market and vibrant trade.
  • D. Makurdi
    Makurdi is the capital city of Benue State in central Nigeria, serving as an important administrative and commercial hub in the region.
  • E. Nnewi
    Nnewi is a major commercial and industrial city in southeastern Nigeria, renowned for its vibrant automotive parts manufacturing and trade.
  • 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_69d8d38974308190a9174430ef256b73 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e543c9d26c8190a80dda411cd0c9ac completed April 19, 2026, 9:06 p.m.
Created at: April 10, 2026, 11:43 a.m.