Triple
T11185220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maybach HL210 P45 |
E264647
|
entity |
| Predicate | powerToWeightRole |
P97746
|
FINISHED |
| Object | powerplant for heavy armored vehicles |
—
|
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: powerplant for heavy armored vehicles | Statement: [Maybach HL210 P45, powerToWeightRole, powerplant for heavy armored vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: powerToWeightRole Context triple: [Maybach HL210 P45, powerToWeightRole, powerplant for heavy armored vehicles]
-
A.
powerToWeightRatio
Indicates the relationship between an entity’s available power and its mass, expressing how much power is provided per unit of weight.
-
B.
vehiclePower
Indicates the amount or type of power a vehicle can produce or is rated to deliver.
-
C.
powerRange
Indicates the range of power values within which an entity operates, applies, or is considered valid.
-
D.
associatedVehicleWeightClass
Indicates the weight classification category that is linked or assigned to a particular vehicle.
-
E.
winnerPowertrainType
Indicates the type of powertrain used by the entity that is identified as the winner in a given context or competition.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8abbeac8190ad6e419258999f4e |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf4461c8190af84060f7db83211 |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:29 p.m.