Triple
T22435216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peugeot e-Expert |
E554602
|
entity |
| Predicate | regulatoryPositioning |
P148174
|
FINISHED |
| Object | zero-emission vehicle |
—
|
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: zero-emission vehicle | Statement: [Peugeot e-Expert, regulatoryPositioning, zero-emission vehicle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulatoryPositioning Context triple: [Peugeot e-Expert, regulatoryPositioning, zero-emission vehicle]
-
A.
regulatoryRecognition
Indicates that an entity has been formally acknowledged or approved by a regulatory authority as meeting specified standards or requirements.
-
B.
regulatoryType
Indicates the specific kind or category of regulatory control, rule, or oversight that applies in the given relationship.
-
C.
regulatoryStructure
Indicates a relationship where one entity serves as a regulatory framework, mechanism, or control system that governs, constrains, or modulates the behavior or operation of another entity.
-
D.
regulatoryAdvantage
Indicates that one entity gains a favorable position or benefit over others due to laws, rules, or regulatory conditions.
-
E.
regulatoryField
Indicates that one entity operates within, is governed by, or is associated with a particular area or domain of regulation defined by another 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15adda0e48190825a5b705ae52d5b |
completed | April 29, 2026, 1:11 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
| PDg | Predicate description generation | batch_69e8aa39e3388190b659d59948ebf3e6 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:47 p.m.