Triple

T534937
Position Surface form Disambiguated ID Type / Status
Subject Yasuhiro Nakasone E12304 entity
Predicate residence P75 FINISHED
Object Tokyo, Japan E5560 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: Tokyo, Japan | Statement: [Yasuhiro Nakasone, residence, Tokyo, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo, Japan
Context triple: [Yasuhiro Nakasone, residence, Tokyo, Japan]
  • A. Tokyo chosen
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • B. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • C. Chiyoda, Tokyo, Japan
    Chiyoda is a central special ward of Tokyo that serves as Japan’s political and administrative heart, housing the Imperial Palace, the National Diet, and many government institutions.
  • D. Minato, Tokyo, Japan
    Minato is a central special ward of Tokyo known for its major business districts, foreign embassies, and landmarks such as Tokyo Tower and Roppongi.
  • E. Shinagawa, Tokyo, Japan
    Shinagawa is a major commercial and transportation hub in southern Tokyo, known for its busy railway station, high-rise office buildings, and waterfront developments along Tokyo Bay.
  • 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_69a4933208e88190891f5debab1b776d completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a496d904408190a2ed16c839017623 completed March 1, 2026, 7:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac93942b1c819087f6fdef027f115e completed March 7, 2026, 9:07 p.m.
Created at: March 1, 2026, 7:32 p.m.