Triple

T11309626
Position Surface form Disambiguated ID Type / Status
Subject 寝屋川市 E267802 entity
Predicate 都市圏 P36084 FINISHED
Object 大阪都市圏 LITERAL 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: 大阪都市圏 | Statement: [寝屋川市, 都市圏, 大阪都市圏]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: 都市圏
Context triple: [寝屋川市, 都市圏, 大阪都市圏]
  • A. urbanAreaType
    Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
  • B. prefecture-levelCity
    Indicates that one entity is a city that holds prefecture-level administrative status in relation to another entity (typically a higher-level region or governing structure).
  • C. city2
    Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
  • D. formsUrbanAreaWith
    Indicates that two or more settlements are geographically and functionally connected so that together they constitute a single continuous urban area.
  • E. metropolitanAreaType chosen
    Indicates the classification of a metropolitan area according to its type or category (e.g., size, function, or administrative status).
  • F. None of above.

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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc completed April 9, 2026, 6:02 p.m.
PD Predicate disambiguation batch_69d787aa31888190860eecaa80da5b20 completed April 9, 2026, 11:04 a.m.
Created at: April 8, 2026, 9:32 p.m.