Triple
T13503093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaguar I-Pace |
E320940
|
entity |
| Predicate | firstAllElectricModelOfBrand |
P110004
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Jaguar I-Pace, firstAllElectricModelOfBrand, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAllElectricModelOfBrand Context triple: [Jaguar I-Pace, firstAllElectricModelOfBrand, yes]
-
A.
firstModel
Indicates that an entity is the initial or earliest model/version in a sequence or series of models.
-
B.
notableElectricVariant
Indicates that one entity is a notable or significant electric-powered version or variant of another entity.
-
C.
firstModelLineOf
Indicates that one entity is the first line of a model or modeling construct associated with another entity.
-
D.
firstModelYearNameplate
Indicates the specific model year in which a particular nameplate (vehicle model designation) was first introduced.
-
E.
electrificationYear
Indicates the year in which something (such as a system, facility, or infrastructure) was converted to or equipped for electric power.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf810e248190a060481004503f96 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
| PDg | Predicate description generation | batch_69dbaee128d88190b097be17fdd2f92b |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:43 p.m.