Triple

T12801623
Position Surface form Disambiguated ID Type / Status
Subject JR Tōkai E306031 entity
Predicate operatesService P5884 FINISHED
Object Kodama E307376 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: Kodama | Statement: [JR Tōkai, operatesService, Kodama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kodama
Context triple: [JR Tōkai, operatesService, Kodama]
  • A. Kodama
    Kodama is a Japanese surname borne by various notable figures in fields such as politics, the military, the arts, and sports.
  • B. Kodama chosen
    Kodama is a Japanese Shinkansen train service known for its all-stop, slower-speed runs along high-speed rail lines such as the Tokaido Shinkansen.
  • C. Moruya
    Moruya is a coastal town in New South Wales, Australia, known for its scenic river setting, nearby beaches, and historic granite quarries.
  • D. Yokadouma
    Yokadouma is a town in eastern Cameroon that serves as an important local administrative and commercial center near the country's forested border regions.
  • E. Asagumo
    Asagumo was a Japanese destroyer of the Imperial Japanese Navy that saw action in World War II, including participation in major Pacific naval engagements.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e7d3f5c8190bf01bef5d263ca26 completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6851143588190b0980e760e030b0b completed May 2, 2026, 11:13 p.m.
Created at: April 9, 2026, 5:30 p.m.