Triple

T20270100
Position Surface form Disambiguated ID Type / Status
Subject Boq E499069 entity
Predicate attends P2636 FINISHED
Object Shiz University 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: Shiz University | Statement: [Boq, attends, Shiz University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shiz University
Context triple: [Boq, attends, Shiz University]
  • A. Shiz University chosen
    Shiz University is a fictional institution of higher learning best known as the primary school setting in Gregory Maguire’s novel "Wicked" and its adaptations.
  • B. Hoshi University
    Hoshi University is a private Japanese university in Tokyo known for its specialized programs in pharmaceutical sciences and related health fields.
  • C. Surugadai University
    Surugadai University is a private Japanese higher education institution located in Hanno, Saitama Prefecture, offering a range of undergraduate and graduate programs.
  • D. Seirei Christopher University
    Seirei Christopher University is a private Christian university in Hamamatsu, Japan, known for its programs in nursing, social work, and related health and welfare fields.
  • E. Osan University
    Osan University is a higher education institution located in Osan, a city in Gyeonggi Province, South Korea.
  • 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_69da6275fa6c8190952924930adee150 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e675dd7c58819095bbf4baeda04d6a completed April 20, 2026, 6:52 p.m.
Created at: April 11, 2026, 11:42 p.m.