Triple

T13570080
Position Surface form Disambiguated ID Type / Status
Subject Nissin Foods E324133 entity
Predicate headquartersLocation P62 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: [Nissin Foods, headquartersLocation, Tokyo, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo, Japan
Context triple: [Nissin Foods, headquartersLocation, Tokyo, Japan]
  • A. Tokyo chosen
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • B. Tokyo
    "Tokyo" is a popular Afrobeats song by Ghanaian singer King Promise featuring Nigerian artist Wizkid.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb00f5b8881908617f42d227ed137 completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f8967288190b822ed1e115f85b2 completed May 3, 2026, 5:02 p.m.
Created at: April 9, 2026, 9:48 p.m.