Triple
T9167184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porsche 911 GT2 RS |
E219988
|
entity |
| Predicate | WeissachPackageFeatures |
P67070
|
FINISHED |
| Object | further weight reduction |
—
|
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: further weight reduction | Statement: [Porsche 911 GT2 RS, WeissachPackageFeatures, further weight reduction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WeissachPackageFeatures Context triple: [Porsche 911 GT2 RS, WeissachPackageFeatures, further weight reduction]
-
A.
featuresVehicle
Indicates that one entity includes, presents, or prominently incorporates a particular vehicle as part of its content, composition, or offering.
-
B.
chassisMaterialFeature
Indicates that an entity has a chassis characterized by a specific material-related feature or property.
-
C.
winnerPowertrainType
Indicates the type of powertrain used by the entity that is identified as the winner in a given context or competition.
-
D.
equipmentCharacteristic
Indicates that a specific characteristic, property, or attribute is associated with a piece of equipment.
-
E.
hasVehicleFeature
chosen
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
- F. None of above.
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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaade47cc81909b5c127dc8aa1340 |
completed | April 1, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69cc6605c6808190a30d92da006206ac |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:22 p.m.