Triple

T7193938
Position Surface form Disambiguated ID Type / Status
Subject General Dynamics E167762 entity
Predicate hasPredecessor P97 FINISHED
Object Canadair E417332 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: Canadair | Statement: [General Dynamics, hasPredecessor, Canadair]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canadair
Context triple: [General Dynamics, hasPredecessor, Canadair]
  • A. Canadair chosen
    Canadair was a Canadian aircraft manufacturer best known for producing specialized amphibious firefighting and utility aircraft before becoming part of Bombardier Aerospace.
  • B. 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.
  • C. 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.
  • D. de Havilland
    De Havilland is the distinguished Anglo-French family name shared by Hollywood actresses Joan Fontaine and her sister Olivia de Havilland.
  • E. 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.
  • 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_69c6888b5248819090499a884ee3ec39 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e9036544819083c70a5d2135ba4b completed March 27, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bf9b8ff48190a561035f754922e9 completed March 28, 2026, 11:46 a.m.
Created at: March 27, 2026, 2:50 p.m.