Triple

T17895139
Position Surface form Disambiguated ID Type / Status
Subject Sm6 Pendolino E447413 entity
Predicate serviceName P31939 FINISHED
Object Allegro 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: Allegro | Statement: [Sm6 Pendolino, serviceName, Allegro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Allegro
Context triple: [Sm6 Pendolino, serviceName, Allegro]
  • A. Allegro
    Allegro is a 1947 Rodgers and Hammerstein musical that experiments with nontraditional staging and narrative to follow a man's life from birth through adulthood.
  • B. Allegro chosen
    Allegro is a high-speed passenger train service operating between Russia and Finland under the Russian Railways brand.
  • C. Posun
    Posun is the given name of Yun Posun, a prominent South Korean politician who served as the country’s second president.
  • D. Trot
    Trot is a young girl from L. Frank Baum’s Oz series who becomes a close companion of characters like the Scarecrow and travels on magical adventures in the Land of Oz.
  • E. Scherzos
    Scherzos are a set of four highly virtuosic and dramatic piano pieces by Frédéric Chopin that expanded the scherzo form into large-scale, emotionally intense concert works.
  • 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_69d8b9f59bd48190a6fc925a855b8bac completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49d7eb4f48190951e26975b57873b completed April 19, 2026, 9:16 a.m.
Created at: April 10, 2026, 10:19 a.m.