Triple

T7606546
Position Surface form Disambiguated ID Type / Status
Subject Higashi-Shinjuku Station E180118 entity
Predicate hasCity P316 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: [Higashi-Shinjuku Station, hasCity, Tokyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo
Context triple: [Higashi-Shinjuku Station, hasCity, 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. Kyoto
    Kyoto is a historic Japanese city renowned for its well-preserved temples, traditional wooden houses, and role as the former imperial capital.
  • 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_69c69f3567008190ab01d2ca7b53584a completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9fe10408190b1c12bb8f911cea8 completed March 27, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c87070d8a88190afde21f548d86292 completed March 29, 2026, 12:21 a.m.
Created at: March 27, 2026, 3:54 p.m.