Triple

T7236604
Position Surface form Disambiguated ID Type / Status
Subject Olympic Stadium E155243 entity
Predicate hasLocationExample P69519 FINISHED
Object Nagano, Japan 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: Nagano, Japan | Statement: [Olympic Stadium, hasLocationExample, Nagano, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagano, Japan
Context triple: [Olympic Stadium, hasLocationExample, Nagano, Japan]
  • A. Nagano chosen
    Nagano is a city in central Japan best known internationally for hosting the 1998 Winter Olympic Games.
  • B. Matsumoto, Nagano, Japan
    Matsumoto, Nagano, Japan is a historic castle city in central Honshu known for its scenic alpine setting and as the hometown of avant-garde artist Yayoi Kusama.
  • C. Fujinomiya, Japan
    Fujinomiya, Japan is a city in Shizuoka Prefecture known as a gateway to Mount Fuji and for its scenic views, shrines, and local cuisine.
  • D. Tsuyama, Japan
    Tsuyama, Japan is a historic city in Okayama Prefecture known for its well-preserved castle ruins, traditional townscape, and famous cherry blossom viewing spots.
  • E. Fukuroi, Japan
    Fukuroi, Japan is a city in Shizuoka Prefecture known for its agricultural production, traditional temples, and role as a regional industrial and cultural center.
  • 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_69c688143bfc81908d4176617735e601 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6f04089408190aa20ed6767590ae1 completed March 27, 2026, 9:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cc32d6c48190ae78b3d1227bb868 completed March 28, 2026, 12:40 p.m.
Created at: March 27, 2026, 2:55 p.m.