Triple

T11934289
Position Surface form Disambiguated ID Type / Status
Subject 文京区 E283998 entity
Predicate hasUniversity P113 FINISHED
Object 順天堂大学 E287805 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: 順天堂大学 | Statement: [文京区, hasUniversity, 順天堂大学]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 順天堂大学
Context triple: [文京区, hasUniversity, 順天堂大学]
  • A. 國學院大學
    國學院大學 is a private Japanese university in Tokyo known for its focus on Shinto studies, Japanese history, and traditional culture.
  • B. Juntendo University chosen
    Juntendo University is a prominent private medical and health sciences university in Tokyo, Japan, known for its long history and affiliated hospitals.
  • C. Jikei University School of Medicine
    Jikei University School of Medicine is a private medical school and university in Tokyo, Japan, known for its long history of medical education and affiliated teaching hospitals.
  • D. Keio University School of Medicine
    Keio University School of Medicine is a prestigious Japanese medical school within Keio University, renowned for its research, clinical education, and contributions to advanced medical science.
  • E. Tokyo Medical School
    Tokyo Medical School was a prominent Japanese medical institution in Tokyo that trained many influential physicians and public health leaders in the late 19th and early 20th centuries.
  • 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_69d6ab2ce9c48190b5d39511b524f666 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90306fcf48190a963d2d1932288d1 completed April 10, 2026, 2:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f4407cc2388190b0f849fbeed89ab7 completed May 1, 2026, 5:56 a.m.
Created at: April 8, 2026, 9:45 p.m.