Triple

T9342564
Position Surface form Disambiguated ID Type / Status
Subject Toho E224796 entity
Predicate basedIn P40 FINISHED
Object Tokyo 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 | Statement: [Toho, basedIn, Tokyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo
Context triple: [Toho, basedIn, Tokyo]
  • 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. 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.
  • E. Nakano, Tokyo
    Nakano, Tokyo is a special ward in western Tokyo known for its dense residential neighborhoods, vibrant shopping streets, and pop culture hub around Nakano Broadway.
  • 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_69ca842993248190a79ab06968994b86 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4bb11cd08190b159a6066dd0ebf1 completed April 1, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e351e7a08190b4abb8747a84871b completed April 4, 2026, 10:09 a.m.
Created at: March 30, 2026, 7:40 p.m.