Triple

T8630827
Position Surface form Disambiguated ID Type / Status
Subject CS100 E204396 entity
Predicate manufacturer P490 FINISHED
Object Bombardier Aerospace 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 Aerospace | Statement: [CS100, manufacturer, Bombardier Aerospace]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bombardier Aerospace
Context triple: [CS100, manufacturer, Bombardier Aerospace]
  • 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. de Havilland Aircraft Company
    De Havilland Aircraft Company was a major British aviation manufacturer renowned for designing innovative military and civilian aircraft, including iconic World War II planes.
  • 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_69ca834b903c8190add96cc651e1a477 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc47417e9c819099739ae901449308 completed March 31, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecca2a3e48190b74ed3c948196409 completed April 2, 2026, 8:08 p.m.
Created at: March 30, 2026, 6:27 p.m.