Triple

T1654128
Position Surface form Disambiguated ID Type / Status
Subject Navy Ministry of Japan E35758 entity
Predicate hadHeadquartersLocation P62 FINISHED
Object Tokyo City 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 City | Statement: [Navy Ministry of Japan, hadHeadquartersLocation, Tokyo City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo City
Context triple: [Navy Ministry of Japan, hadHeadquartersLocation, Tokyo City]
  • A. Tokyo chosen
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • B. 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.
  • C. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • D. Shibuya City
    Shibuya City is a major commercial and entertainment district in central Tokyo, Japan, famous for its bustling scramble crossing, youth culture, and fashion scene.
  • E. 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.
  • 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_69a8860568888190a32cd9f70acbba42 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61e142ac8190aa2fbd8f0826b5b2 completed March 6, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc61b715c81908bb4849b03617d85 completed March 10, 2026, 7:19 a.m.
Created at: March 4, 2026, 7:29 p.m.