Triple

T2868513
Position Surface form Disambiguated ID Type / Status
Subject Tokaido Shinkansen E63499 entity
Predicate connectsCity P4245 FINISHED
Object Osaka E486 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: Osaka | Statement: [Tokaido Shinkansen, connectsCity, Osaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Osaka
Context triple: [Tokaido Shinkansen, connectsCity, Osaka]
  • A. Osaka chosen
    Osaka is Japan's third-largest city and a major economic, cultural, and historical hub known for its vibrant street food, bustling nightlife, and role as a commercial center in the Kansai region.
  • B. Nagoya
    Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
  • C. Higashiōsaka
    Higashiōsaka is an industrial and residential city in Japan known for its manufacturing base and location within the Osaka metropolitan area.
  • D. Suita, Osaka
    Suita, Osaka is a city in northern Osaka Prefecture, Japan, known as a major suburban and educational hub that hosts the main campus of Osaka University.
  • E. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • 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_69b085ebb1e481909c27fa8a8e2ee1c6 completed March 10, 2026, 8:58 p.m.
Created at: March 6, 2026, 10:02 p.m.