Triple

T3040236
Position Surface form Disambiguated ID Type / Status
Subject Nagoya City Hall E83106 entity
Predicate operator P179 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 Hall, operator, City of Nagoya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Nagoya
Context triple: [Nagoya City Hall, operator, 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. 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.
  • C. Shibuya City
    Shibuya City is a major commercial and entertainment district in central Tokyo, Japan, famous for its bustling scramble crossing, youth culture, and fashion scene.
  • D. Yokkaichi
    Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
  • E. Namba City
    Namba City is a large shopping and entertainment complex in Osaka’s Namba district, featuring retail stores, restaurants, offices, and a rooftop garden integrated with the surrounding urban landscape.
  • 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_69ad8b2298908190a7cb4e9bdbf064d0 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9b59fea8819091796e30812df9c5 completed March 8, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdf9e0af508190adbd16c718d996e2 completed March 21, 2026, 1:52 a.m.
Created at: March 8, 2026, 3:01 p.m.