Triple

T12716050
Position Surface form Disambiguated ID Type / Status
Subject Takeo Fukuda E303840 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: [Takeo Fukuda, residence, Tokyo, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo, Japan
Context triple: [Takeo Fukuda, residence, Tokyo, Japan]
  • A. Tokyo
    "Tokyo" is a popular Afrobeats song by Ghanaian singer King Promise featuring Nigerian artist Wizkid.
  • B. Tokyo chosen
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • C. Ōta, Tokyo
    Ōta, Tokyo is a large ward in southern Tokyo known for its mix of residential and industrial areas and for hosting Haneda Airport, one of Japan’s major international gateways.
  • D. Tōkyō-wan
    Tōkyō-wan is the Japanese name for Tokyo Bay, a major urban bay on the Pacific coast of Honshu that serves as a key economic and transportation hub for the Greater Tokyo Area.
  • E. Chuo City, Tokyo
    Chuo City, Tokyo is a central ward of Tokyo known for its historic commercial districts like Nihonbashi and Ginza, serving as a major hub for finance, retail, and culture.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9620bd6148190a2f50067a4c18c14 completed April 10, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8c37eb08190a4c15cb50f84c341 completed May 3, 2026, 2:53 a.m.
Created at: April 9, 2026, 5:23 p.m.