Triple
T136186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saab Automobile |
E2751
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Saab AB |
E15976
|
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: Saab AB | Statement: [Saab Automobile, foundedBy, Saab AB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saab AB Context triple: [Saab Automobile, foundedBy, Saab AB]
-
A.
Saab AB
chosen
Saab AB is a Swedish aerospace and defense company known for developing military aircraft, advanced defense systems, and security solutions.
-
B.
Saab Automobile
Saab Automobile was a Swedish car manufacturer known for its innovative engineering, turbocharged engines, and distinctive, safety-focused designs.
-
C.
Thomson SA
Thomson SA was a major French electronics and media conglomerate known for its consumer electronics, broadcasting, and defense-related technologies.
-
D.
SAIC Motor
SAIC Motor is a major Chinese state-owned automotive manufacturer and one of the country’s largest carmakers, producing vehicles under its own brands and through joint ventures with global and regional partners.
-
E.
Airbus
Airbus is a major European aerospace corporation known for designing and manufacturing commercial airliners such as the A320, A330, and A380 families.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a4edf081908c494c8370c76b9a |
completed | Feb. 28, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2b85fe4d481909e39b745857b62e7 |
completed | Feb. 28, 2026, 9:41 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.