Triple

T3131939
Position Surface form Disambiguated ID Type / Status
Subject Shinkansen high-speed rail network E65434 entity
Predicate connectsCity P4245 FINISHED
Object Nagoya E11598 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: Nagoya | Statement: [Shinkansen high-speed rail network, connectsCity, Nagoya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagoya
Context triple: [Shinkansen high-speed rail network, connectsCity, 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. 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.
  • D. Yokkaichi
    Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
  • E. Kitakyushu
    Kitakyushu is a major industrial and port city located in Fukuoka Prefecture on Japan’s Kyushu island.
  • 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_69ad8581c25c8190b0d85ba9b9baa531 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada55f77b881908866fc43bdb18185 completed March 8, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06886d748190b346a1f4cc2b6f10 completed March 21, 2026, 8:58 p.m.
Created at: March 8, 2026, 3:04 p.m.