Triple

T17118579
Position Surface form Disambiguated ID Type / Status
Subject M200 series trains E415403 entity
Predicate manufacturer P490 FINISHED
Object Bombardier E97324 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: Bombardier | Statement: [M200 series trains, manufacturer, Bombardier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bombardier
Context triple: [M200 series trains, manufacturer, Bombardier]
  • A. Bombardier chosen
    Bombardier is a major Canadian manufacturer of trains and rail equipment widely used by transit agencies around the world.
  • B. De Havilland Canada
    De Havilland Canada is a Canadian aircraft manufacturer best known for its rugged short takeoff and landing (STOL) regional and utility aircraft used worldwide.
  • C. Canadair
    Canadair was a Canadian aircraft manufacturer best known for producing specialized amphibious firefighting and utility aircraft before becoming part of Bombardier Aerospace.
  • D. Hawker Siddeley Canada
    Hawker Siddeley Canada was a Canadian railcar and aerospace manufacturer known for producing passenger rail coaches and other transportation equipment.
  • E. Avro Canada
    Avro Canada was a Canadian aircraft manufacturing company best known for advanced military and experimental aircraft projects such as the CF-100 Canuck and the Avro Arrow.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3e8086a388190a655a044feccab14 completed April 18, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a014147db18819083e6cfbb597687c1 completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:35 a.m.