Triple

T1746394
Position Surface form Disambiguated ID Type / Status
Subject Nagano Olympic Stadium E38344 entity
Predicate governingBody P46 FINISHED
Object City of Nagano E78933 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 Nagano | Statement: [Nagano Olympic Stadium, governingBody, City of Nagano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Nagano
Context triple: [Nagano Olympic Stadium, governingBody, City of Nagano]
  • A. Nagano chosen
    Nagano is a city in central Japan best known internationally for hosting the 1998 Winter Olympic Games.
  • B. Kameoka
    Kameoka is a city in Kyoto Prefecture, Japan, known for its rural landscapes, historical sites, and proximity to Kyoto.
  • C. Daikanyama
    Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
  • D. Yamagata
    Yamagata is a city in northern Japan that serves as the capital of Yamagata Prefecture, known for its hot springs, winter sports, and cherry production.
  • E. Kyotanabe
    Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
  • 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_69a8862b01a48190ab47209063af82d9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63eabdf48190878ecde3d1b1faf3 completed March 6, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada9866d308190a1de483f5a330362 completed March 8, 2026, 4:53 p.m.
Created at: March 4, 2026, 7:31 p.m.