Triple

T14083555
Position Surface form Disambiguated ID Type / Status
Subject Series E5 Shinkansen E338930 entity
Predicate operatorService P5884 FINISHED
Object Yamabiko 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: Yamabiko | Statement: [Series E5 Shinkansen, operatorService, Yamabiko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yamabiko
Context triple: [Series E5 Shinkansen, operatorService, Yamabiko]
  • A. Yamabiko chosen
    Yamabiko is a high-speed Shinkansen train service in Japan that operates on the Tōhoku Shinkansen line, connecting Tokyo with northern regions such as Sendai.
  • B. Shimotsuki
    Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
  • C. Taku-shi
    Taku-shi is a city located in Saga Prefecture on Japan’s Kyushu island, known for its historical sites and rural landscapes.
  • D. Yamakoshi
    Yamakoshi is a recurring character from the Disney XD sitcom "Pair of Kings," known as a mystical fish with prophetic abilities and a quirky, comedic presence.
  • E. Sugano no Mamichi
    Sugano no Mamichi was an 8th-century Japanese court noble and scholar of the Nara period, known for his role in government and contributions to classical historiography.
  • 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_69d81c687b0c819087fd9ed4198403f8 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5ede40048190b465e909565730c1 completed April 14, 2026, 3:35 p.m.
Created at: April 9, 2026, 10:21 p.m.