Triple

T2390621
Position Surface form Disambiguated ID Type / Status
Subject Keio Medical Science Prize E48932 entity
Predicate location P40 FINISHED
Object Japan E174 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: Japan | Statement: [Keio Medical Science Prize, location, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japan
Context triple: [Keio Medical Science Prize, location, Japan]
  • A. Japan chosen
    Japan is an East Asian island nation in the Pacific Ocean known for its advanced technology, rich cultural heritage, and major cities such as Tokyo, Osaka, and Kyoto.
  • B. Ota, Japan
    Ōta is a special ward in Tokyo, Japan, known for Haneda Airport, its coastal location on Tokyo Bay, and a mix of residential, industrial, and commercial districts.
  • C. Honshu
    Honshu is the largest and most populous island of Japan, home to major cities such as Tokyo, Osaka, and Kyoto.
  • D. South Korea
    South Korea is an East Asian nation on the southern half of the Korean Peninsula, known for its advanced technology, vibrant pop culture, and rapid economic development.
  • E. Kore
    Kore is an alternate name for Persephone, the Greek goddess associated with spring’s growth and the queen of the underworld.
  • 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_69a88aa5f63081908d07fd302029fcbd completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc87457388190822d5506327db8f2 completed March 7, 2026, 6:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3d4f0608190bcc77a67fa85b963 completed March 9, 2026, 11:49 a.m.
Created at: March 4, 2026, 7:57 p.m.