Triple

T11407291
Position Surface form Disambiguated ID Type / Status
Subject Tokyo International Forum E270271 entity
Predicate near P350 FINISHED
Object Tokyo Station NE NERFINISHED

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 Station | Statement: [Tokyo International Forum, near, Tokyo Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo Station
Context triple: [Tokyo International Forum, near, Tokyo Station]
  • A. Tokyo Station chosen
    Tokyo Station is a major railway hub in central Tokyo, serving as a key terminal for Shinkansen bullet trains and numerous local and regional lines.
  • B. Yokohama Station
    Yokohama Station is one of Japan’s busiest railway hubs, serving numerous JR, private, and subway lines in central Yokohama.
  • C. Shibuya Station
    Shibuya Station is one of Tokyo’s busiest and most important railway hubs, serving multiple train and subway lines and anchoring the famous Shibuya shopping and entertainment district.
  • D. Kyoto Station
    Kyoto Station is a major railway and transportation hub in Kyoto, Japan, known for its vast, modern architectural complex that integrates trains, buses, shopping, and cultural facilities.
  • E. Shinjuku Station
    Shinjuku Station is one of the world’s busiest railway hubs, serving as a major commercial and transportation center in Tokyo, Japan.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d6aaddeaa8819088b30ef7b50598c9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8014c820c81908538ba4a08e13230 completed April 9, 2026, 7:43 p.m.
Created at: April 8, 2026, 9:34 p.m.