Triple

T15496495
Position Surface form Disambiguated ID Type / Status
Subject Tokoname E378830 entity
Predicate railwayOperator P5620 FINISHED
Object Meitetsu E320648 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: Meitetsu | Statement: [Tokoname, railwayOperator, Meitetsu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meitetsu
Context triple: [Tokoname, railwayOperator, Meitetsu]
  • A. Meitetsu chosen
    Meitetsu is a major private railway company in Japan’s Chubu region, best known for operating extensive rail and transport services centered around Nagoya.
  • B. Keihan
    Keihan is a major Japanese private railway operator serving the Osaka–Kyoto region with commuter and interurban rail services.
  • C. Mantetsu
    Mantetsu was a powerful Japanese state-controlled railway and colonial enterprise that operated rail lines and managed extensive economic activities in Manchuria during the early 20th century.
  • D. Odakyu
    Odakyu is a Japanese retail and transportation company best known for operating railway lines and department stores in the Greater Tokyo area.
  • E. Shinkankakuha
    Shinkankakuha was a Japanese literary movement of the early 20th century that sought to capture fresh, immediate sensory experience and psychological nuance through innovative narrative techniques.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03faecd60819091eeaa56c9c8f67d completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3665769c8190be1af51a82a5e75f completed May 9, 2026, 1:28 p.m.
Created at: April 10, 2026, 3:52 a.m.