Triple

T1336087
Position Surface form Disambiguated ID Type / Status
Subject Akinobu Okada E28751 entity
Predicate countryOfWork P1527 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: [Akinobu Okada, countryOfWork, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japan
Context triple: [Akinobu Okada, countryOfWork, 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. Honshu
    Honshu is the largest and most populous island of Japan, home to major cities such as Tokyo, Osaka, and Kyoto.
  • C. 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.
  • D. Fujinomiya, Japan
    Fujinomiya, Japan is a city in Shizuoka Prefecture known as a gateway to Mount Fuji and for its scenic views, shrines, and local cuisine.
  • E. Oppama, Japan
    Oppama, Japan is an industrial coastal district in Yokosuka, Kanagawa Prefecture, best known for its major Nissan automobile manufacturing plant.
  • 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_69a498561a508190a3e1bc137c2b866a completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1ecb5208190a9eadda113c91e66 completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc6255b808190823bc240365ed304 completed March 8, 2026, 12:43 a.m.
Created at: March 1, 2026, 7:55 p.m.