Triple
T136183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saab Automobile |
E2751
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Saab |
E2751
|
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 | Statement: [Saab Automobile, brand, Saab]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saab Context triple: [Saab Automobile, brand, Saab]
-
A.
Saab Automobile
chosen
Saab Automobile was a Swedish car manufacturer known for its innovative engineering, turbocharged engines, and distinctive, safety-focused designs.
-
B.
Saab AB
Saab AB is a Swedish aerospace and defense company known for developing military aircraft, advanced defense systems, and security solutions.
-
C.
Mercedes-Benz
Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
-
D.
BMW
BMW is a German luxury automobile and motorcycle manufacturer renowned for its performance-oriented vehicles and engineering.
-
E.
Packard
Packard is a surname most prominently associated with David Packard, the American electrical engineer and co-founder of Hewlett-Packard.
- 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_69a2b4bad1a0819098459e2a9d6b8d2a |
completed | Feb. 28, 2026, 9:26 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.