Triple

T13574846
Position Surface form Disambiguated ID Type / Status
Subject Nagoya City Transportation Bureau E324253 entity
Predicate parentOrganization P254 FINISHED
Object City of Nagoya E11598 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: City of Nagoya | Statement: [Nagoya City Transportation Bureau, parentOrganization, City of Nagoya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Nagoya
Context triple: [Nagoya City Transportation Bureau, parentOrganization, City of Nagoya]
  • A. Nagoya chosen
    Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
  • B. City of Osaka
    The City of Osaka is a major Japanese metropolis and commercial hub known for its modern architecture, vibrant street food culture, and historical landmarks.
  • C. Osaki City
    Osaki City is a regional city in northeastern Japan known for its agricultural production, hot springs, and historical sites.
  • D. Shizuoka City, Japan
    Shizuoka City, Japan is a coastal city in central Honshu known for its views of Mount Fuji, green tea production, and role as a regional economic and cultural center.
  • E. Nanyo City
    Nanyo City is a municipality in northeastern Japan known for its hot springs, fruit production, and scenic rural landscapes.
  • 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb02b1f108190a12af382d1de70bb completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde15abe6c8190a6212861bbce790e completed May 8, 2026, 1:12 p.m.
Created at: April 9, 2026, 9:48 p.m.