Triple

T2821257
Position Surface form Disambiguated ID Type / Status
Subject Setsunan University E54814 entity
Predicate nativeName P15 FINISHED
Object 摂南大学 E267809 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: 摂南大学 | Statement: [Setsunan University, nativeName, 摂南大学]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 摂南大学
Context triple: [Setsunan University, nativeName, 摂南大学]
  • A. 摂南大学 chosen
    摂南大学は、大阪府に本部を置き、薬学部や理工学部などを擁する私立総合大学です。
  • B. Kansai Gaidai University
    Kansai Gaidai University is a private Japanese university renowned for its programs in foreign languages, international studies, and study-abroad opportunities.
  • C. 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.
  • D. Nagoya City University
    Nagoya City University is a public university in Nagoya, Japan, known for its programs in medicine, pharmaceutical sciences, design, and humanities.
  • E. Niigata University
    Niigata University is a national research university in Niigata, Japan, known for its comprehensive programs across humanities, sciences, engineering, and medical fields.
  • 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde6e85008190a08eb2bf8e393e7e completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69afcea809e48190b22f25a3c8c1acdd completed March 10, 2026, 7:56 a.m.
Created at: March 6, 2026, 9:59 p.m.