Triple
T17914421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renault 4 |
E447888
|
entity |
| Predicate | approximateUnitsProduced |
P99700
|
FINISHED |
| Object | over 8 million |
—
|
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: over 8 million | Statement: [Renault 4, approximateUnitsProduced, over 8 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateUnitsProduced Context triple: [Renault 4, approximateUnitsProduced, over 8 million]
-
A.
approximateProductionNumber
chosen
Indicates that one entity specifies an estimated or non-exact quantity associated with the production output of another entity.
-
B.
totalProduction
Indicates the overall quantity of goods, services, or output produced by an entity or system over a specified period or within a defined scope.
-
C.
approximateMass
Indicates that one entity has a mass value that is an estimate or close approximation of the mass of another entity.
-
D.
designedApproximately
Indicates that one entity was created, planned, or engineered to an estimated or imprecise degree in relation to another entity or specification.
-
E.
approximateWeightInPounds
Indicates the estimated weight of an entity expressed in pounds, rather than an exact measured value.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a30461848190b932a45807329216 |
completed | April 19, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:20 a.m.