Triple

T8089731
Position Surface form Disambiguated ID Type / Status
Subject Hokuriku Shinkansen E188825 entity
Predicate connectsCity P4245 FINISHED
Object 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: Nagano | Statement: [Hokuriku Shinkansen, connectsCity, Nagano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagano
Context triple: [Hokuriku Shinkansen, connectsCity, Nagano]
  • A. Nagano chosen
    Nagano is a city in central Japan best known internationally for hosting the 1998 Winter Olympic Games.
  • B. Niigata
    Niigata is a major coastal city in north-central Japan known for its important seaport on the Sea of Japan, rice production, and sake brewing.
  • C. Nagano Prefecture
    Nagano Prefecture is a mountainous region in central Japan renowned for its ski resorts, natural scenery, and role as the venue of the 1998 Winter Olympics.
  • D. Toyama
    Toyama is a coastal city in central Japan known as the capital of Toyama Prefecture, serving as a regional industrial and transportation hub on the Sea of Japan.
  • E. Oita
    Ōita is a coastal city on Japan’s Kyushu island known for its hot springs, regional cuisine, and role as the capital of Ōita Prefecture.
  • 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb421e30e88190b9699b338b69b81c completed March 31, 2026, 3:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd677b00548190929a2a38b4d1476f completed April 1, 2026, 6:44 p.m.
Created at: March 30, 2026, 5:29 p.m.