Triple
T5841847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ADtranz |
E129611
|
entity |
| Predicate | acquiredBy |
P347
|
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: [ADtranz, acquiredBy, Bombardier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bombardier Context triple: [ADtranz, acquiredBy, Bombardier]
-
A.
Bombardier
chosen
Bombardier is a major Canadian manufacturer of trains and rail equipment widely used by transit agencies around the world.
-
B.
Canadair
Canadair was a Canadian aircraft manufacturer best known for producing specialized amphibious firefighting and utility aircraft before becoming part of Bombardier Aerospace.
-
C.
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.
-
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.
Embraer
Embraer is a Brazilian aerospace company best known globally for designing and manufacturing regional and business jets used by airlines and operators worldwide.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c034d876fc819089818c731116af56 |
completed | March 22, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a1a2506481908a3e638c1121bfd0 |
completed | March 23, 2026, 2:12 a.m. |
Created at: March 22, 2026, 3:54 p.m.