Triple

T22407276
Position Surface form Disambiguated ID Type / Status
Subject Federal University of Technology Akure E553909 entity
Predicate locatedIn P40 FINISHED
Object Akure 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: Akure | Statement: [Federal University of Technology Akure, locatedIn, Akure]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akure
Context triple: [Federal University of Technology Akure, locatedIn, Akure]
  • A. Akure chosen
    Akure is the capital city of Ondo State in southwestern Nigeria, known as an important administrative and commercial center in the region.
  • B. Aulestad
    Aulestad is the historic Norwegian country estate and museum best known as the longtime home of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
  • C. Sandvika
    Sandvika is a town in southeastern Norway that serves as the administrative center of Bærum and a commercial hub in the Greater Oslo Region.
  • D. Oedheim
    Oedheim is a small municipality in the Heilbronn district of Baden-Württemberg in southern Germany.
  • E. Esteio
    Esteio is a municipality in the state of Rio Grande do Sul in southern Brazil, known for its industrial activity and for hosting one of the country’s major agricultural fairs.
  • 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_69e11e4da7048190b4387d422a9a0de5 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f158ba1c6481908e4b9b3635ed3a49 completed April 29, 2026, 1:02 a.m.
Created at: April 16, 2026, 8:46 p.m.