Triple

T13416270
Position Surface form Disambiguated ID Type / Status
Subject Nagano Electric Railway E313222 entity
Predicate operatesIn P82 FINISHED
Object Nagano City 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: Nagano City | Statement: [Nagano Electric Railway, operatesIn, Nagano City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagano City
Context triple: [Nagano Electric Railway, operatesIn, Nagano City]
  • A. Nagano chosen
    Nagano is a city in central Japan best known internationally for hosting the 1998 Winter Olympic Games.
  • B. Fuji City
    Fuji City is an industrial city in Shizuoka Prefecture, Japan, known for its paper manufacturing industry and views of nearby Mount Fuji.
  • C. Yamagata City
    Yamagata City is a regional hub in northeastern Japan known for its hot springs, surrounding mountains, and annual Hanagasa Festival.
  • D. 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.
  • E. Maebashi
    Maebashi is the capital city of Gunma Prefecture in Japan, known as a regional administrative and commercial center on the Kantō Plain.
  • 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_69d806ad0c44819088833ae1ec9e9690 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaeb6e904819098cc9153fd2feaf5 completed April 12, 2026, 2:39 p.m.
Created at: April 9, 2026, 9:39 p.m.