Triple

T20414436
Position Surface form Disambiguated ID Type / Status
Subject Nagoya Golden Dragons E500670 entity
Predicate location P40 FINISHED
Object Nagoya 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: Nagoya | Statement: [Nagoya Golden Dragons, location, Nagoya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagoya
Context triple: [Nagoya Golden Dragons, location, 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. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • C. Nankoku City
    Nankoku City is a regional city on the island of Shikoku in Japan, known for its agricultural production and proximity to the city of Kōchi.
  • D. Osaka
    Osaka is Japan's third-largest city and a major economic, cultural, and historical hub known for its vibrant street food, bustling nightlife, and role as a commercial center in the Kansai region.
  • E. Toyohashi
    Toyohashi is a city in Aichi Prefecture, Japan, known as a regional commercial and transportation hub on the Pacific coast of central Honshu.
  • 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_69e0b4a935588190b9446a99b37ced44 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67a4281048190a2b016ec16b7d203 completed April 20, 2026, 7:10 p.m.
Created at: April 16, 2026, 11:30 a.m.