Triple

T21372387
Position Surface form Disambiguated ID Type / Status
Subject Showa University E527098 entity
Predicate hasAbbreviation P43 FINISHED
Object Showa Univ. 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: Showa Univ. | Statement: [Showa University, hasAbbreviation, Showa Univ.]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Showa Univ.
Context triple: [Showa University, hasAbbreviation, Showa Univ.]
  • A. Showa University chosen
    Showa University is a private Japanese university known for its strong focus on medical and health sciences education and research.
  • B. Shokei University
    Shokei University is a private higher education institution located in Kumamoto, Japan, known for its focus on humanities, education, and community-oriented studies.
  • C. Seisen University
    Seisen University is a private Catholic liberal arts university in Tokyo, Japan, known for its focus on humanities, global studies, and education.
  • D. Seikei University
    Seikei University is a private Japanese university in Tokyo known for educating several prominent political and business leaders, including former Prime Minister Shinzo Abe.
  • E. Toyo University
    Toyo University is a private Japanese university known for its comprehensive academic programs and active participation in collegiate athletics.
  • 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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0b0d5ec81908da8f38380dbdc7a completed April 22, 2026, 11:27 a.m.
Created at: April 16, 2026, 5:10 p.m.