Triple

T16059487
Position Surface form Disambiguated ID Type / Status
Subject Buzan-ha E389568 entity
Predicate associatedCountry P1083 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: [Buzan-ha, associatedCountry, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japan
Context triple: [Buzan-ha, associatedCountry, 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. Japo
    Japo is a small settlement located on Arno Atoll in the Marshall Islands.
  • C. 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.
  • D. Japan and America
    "Japan and America" is a comparative cultural and critical work by Yone Noguchi examining the relationships, contrasts, and mutual perceptions between Japanese and American societies.
  • E. Honshu
    Honshu is the largest and most populous island of Japan, home to major cities such as Tokyo, Osaka, and Kyoto.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837729e4819086e7429e0a76b0d7 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbe49bd0819088e25de082184133 completed May 10, 2026, 1:14 a.m.
Created at: April 10, 2026, 4:57 a.m.