Triple

T2871638
Position Surface form Disambiguated ID Type / Status
Subject Osun State E63575 entity
Predicate hasMajorCity P316 FINISHED
Object Iragbiji E303980 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: Iragbiji | Statement: [Osun State, hasMajorCity, Iragbiji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Iragbiji
Context triple: [Osun State, hasMajorCity, Iragbiji]
  • A. Iragbiji chosen
    Iragbiji is a prominent town in southwestern Nigeria, recognized as one of the key urban centers of the Ijesha people in Osun State.
  • B. Ikwuano
    Ikwuano is a local government area in southeastern Nigeria known for its predominantly agrarian communities and cultural heritage within Abia State.
  • C. Nasar
    Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
  • D. Iraq
    Iraq is a Middle Eastern country historically significant for its ancient Mesopotamian civilizations and its major role in 20th- and 21st-century geopolitics and conflicts.
  • E. Abckiria
    Abckiria is a 16th-century Finnish primer and religious text by Mikael Agricola, regarded as the first book printed in the Finnish language.
  • 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_69ab4c42fb8c8190b36e161d47c03b81 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdfe46a1c819084399a191f0dfe9c completed March 7, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01db01d348190945ab982ce5c5b2d completed March 10, 2026, 1:33 p.m.
Created at: March 6, 2026, 10:02 p.m.