Triple

T1925287
Position Surface form Disambiguated ID Type / Status
Subject Osaka–Kobe metropolitan area E40815 entity
Predicate majorCity P316 FINISHED
Object Takatsuki E9377 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: Takatsuki | Statement: [Osaka–Kobe metropolitan area, majorCity, Takatsuki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Takatsuki
Context triple: [Osaka–Kobe metropolitan area, majorCity, Takatsuki]
  • A. Takatsuki chosen
    Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
  • B. Wakatsuki
    Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
  • C. Suzuya
    Suzuya is a Japanese Mogami-class heavy cruiser of the Imperial Japanese Navy that served during World War II.
  • D. Kamiyama
    Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
  • E. Marunouchi
    Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
  • 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_69a8864711648190b07bed24ed76258e completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb260da088190ac53bfc9437e112b completed March 7, 2026, 5:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69b333ef7f30819086b538cdc2cefe0f completed March 12, 2026, 9:45 p.m.
Created at: March 4, 2026, 7:35 p.m.