Triple

T12187805
Position Surface form Disambiguated ID Type / Status
Subject 天野浩 E290379 entity
Predicate employer P7 FINISHED
Object 名古屋大学 E11599 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: 名古屋大学 | Statement: [天野浩, employer, 名古屋大学]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 名古屋大学
Context triple: [天野浩, employer, 名古屋大学]
  • A. Nagoya University chosen
    Nagoya University is a prestigious Japanese national research university known for its strong science and engineering programs and several Nobel Prize–winning scholars.
  • B. Nagoya City University
    Nagoya City University is a public university in Nagoya, Japan, known for its programs in medicine, pharmaceutical sciences, design, and humanities.
  • C. 近畿大学
    近畿大学は、大阪府東大阪市に本部を置き、多数の学部とキャンパスを持つ日本の私立総合大学です。
  • D. 京都帝国大学
    京都帝国大学 was a major prewar Japanese imperial university in Kyoto that later became Kyoto University, renowned for its research and academic excellence.
  • E. Yokohama National University
    Yokohama National University is a prominent Japanese national research university located in Yokohama, known for its programs in engineering, economics, business, and education.
  • 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_69d6ab64de5881908d56eb7a75c6cc69 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d916012c2c819085824332ad60059e completed April 10, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6b0a84c8190ae593e368c13b5a5 completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:50 p.m.