Triple

T18576021
Position Surface form Disambiguated ID Type / Status
Subject University of Nigeria, Nsukka E453989 entity
Predicate shortName P43 FINISHED
Object UNN 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: UNN | Statement: [University of Nigeria, Nsukka, shortName, UNN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UNN
Context triple: [University of Nigeria, Nsukka, shortName, UNN]
  • A. UNN chosen
    UNN is the commonly used acronym for the University of Nigeria, Nsukka, one of Nigeria’s leading federal universities.
  • B. UNNM
    UNNM is the acronym for the United Nations Network on Migration, a UN coordination mechanism focused on safe, orderly, and regular migration.
  • C. NNU
    NNU is a comprehensive public university in Nanjing, China, known for its strong programs in teacher education, humanities, and sciences.
  • D. UNNT
    UNNT is the ICAO airport code for Tolmachevo Airport, the main international airport serving Novosibirsk in Russia.
  • E. UNLU
    UNLU is the acronym for the Unified National Leadership of the Uprising, a coordinating body of Palestinian factions that directed much of the first Intifada against Israeli occupation in the late 1980s.
  • 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.