Triple
T5509981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daimler-Benz DB 600 |
E144537
|
entity |
| Predicate | crankshaftType |
P65156
|
FINISHED |
| Object | one-piece forged steel crankshaft |
—
|
LITERAL 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: one-piece forged steel crankshaft | Statement: [Daimler-Benz DB 600, crankshaftType, one-piece forged steel crankshaft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crankshaftType Context triple: [Daimler-Benz DB 600, crankshaftType, one-piece forged steel crankshaft]
-
A.
engineTypeUsed
Indicates that a particular type of engine is employed or utilized in relation to a specified entity or system.
-
B.
shaftCount
Indicates the number of shafts associated with or contained in an object or system.
-
C.
cylinderHeadBrand
Indicates the brand or manufacturer associated with a cylinder head.
-
D.
hasBoreType
Indicates that an entity is characterized by or associated with a specific type of bore (e.g., cylindrical, tapered, rifled).
-
E.
numberOfCylinders
Indicates the count of engine cylinders associated with an entity.
- F. None of above. chosen
Provenance (4 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_69c008f6b5048190a09064116062cf69 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f4ba90c8190ad22e5de84c545f9 |
completed | March 22, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69c01b07bde08190b3933b96bdc70dd5 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f051e508190b3886d87b4afdd0b |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:33 p.m.