Triple

T2868516
Position Surface form Disambiguated ID Type / Status
Subject Tokaido Shinkansen E63499 entity
Predicate startStation P389 FINISHED
Object Tokyo Station E34204 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 Station | Statement: [Tokaido Shinkansen, startStation, Tokyo Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo Station
Context triple: [Tokaido Shinkansen, startStation, 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 (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_69ab4c42fb8c8190b36e161d47c03b81 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdfdfef1881909dc52a1b34cd24e3 completed March 7, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69c6cad46d4081908f685d961d100d42 completed March 27, 2026, 6:22 p.m.
Created at: March 6, 2026, 10:02 p.m.