Triple

T14680073
Position Surface form Disambiguated ID Type / Status
Subject Higashiyodogawa-ku, Osaka E344753 entity
Predicate adjacentTo P224 FINISHED
Object Suita City 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: Suita City | Statement: [Higashiyodogawa-ku, Osaka, adjacentTo, Suita City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suita City
Context triple: [Higashiyodogawa-ku, Osaka, adjacentTo, Suita City]
  • A. Suita City chosen
    Suita City is a municipality in Osaka Prefecture, Japan, known as a residential and commercial hub within the Osaka metropolitan area and home to attractions such as the Expo ’70 Commemorative Park.
  • B. Osaki City
    Osaki City is a regional city in northeastern Japan known for its agricultural production, hot springs, and historical sites.
  • C. Settsu City
    Settsu City is a suburban municipality in northern Osaka Prefecture, Japan, known for its residential neighborhoods and convenient access to central Osaka.
  • D. Osaki New City
    Osaki New City is a major business and commercial district in Tokyo known for its modern office complexes, high-rise buildings, and urban redevelopment projects.
  • E. Bunkyō City
    Bunkyō City is a special ward in central Tokyo, Japan, known for its universities, historic temples, and quiet residential neighborhoods.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb5692284819090f775be8e478522 completed April 14, 2026, 9:45 p.m.
Created at: April 10, 2026, 1:27 a.m.