Triple

T21831158
Position Surface form Disambiguated ID Type / Status
Subject British Rail Class 90 E538996 entity
Predicate hasNickName P39 FINISHED
Object Skoda 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: Skoda | Statement: [British Rail Class 90, hasNickName, Skoda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skoda
Context triple: [British Rail Class 90, hasNickName, Skoda]
  • A. Škoda
    Škoda is a Czech automobile manufacturer known for producing practical, affordable cars and operating as a subsidiary brand within the Volkswagen Group.
  • B. Škoda Scala
    The Škoda Scala is a compact hatchback introduced by the Czech automaker Škoda Auto, positioned between the Fabia and Octavia and known for its practicality, spacious interior, and modern technology features.
  • C. Škoda Karoq
    The Škoda Karoq is a compact crossover SUV produced by the Czech automaker Škoda, known for its practical interior, efficient engines, and family-friendly versatility.
  • D. Škoda Varsovia
    Škoda Varsovia is a type of modern metro train built by Škoda for use on the Warsaw Metro system.
  • E. Škoda Electric chosen
    Škoda Electric is a Czech manufacturer specializing in electric public transport vehicles and equipment, particularly trolleybuses and related traction systems.
  • 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_69e0c475cda88190987d08f23caebdc1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f091362d9081909f00ad7a2806d5cb completed April 28, 2026, 10:51 a.m.
Created at: April 16, 2026, 6:55 p.m.