Triple
T23333333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LAV (leisure activity vehicle) |
E591504
|
entity |
| Predicate | usedInMarketingLanguageOf |
P86932
|
FINISHED |
| Object | European car manufacturers |
—
|
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: European car manufacturers | Statement: [LAV (leisure activity vehicle), usedInMarketingLanguageOf, European car manufacturers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInMarketingLanguageOf Context triple: [LAV (leisure activity vehicle), usedInMarketingLanguageOf, European car manufacturers]
-
A.
usedInMarketingMaterials
Indicates that something is included or featured as part of marketing or promotional materials.
-
B.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
C.
usedInBrand
Indicates that something (such as a component, material, or element) is utilized as part of or within a particular brand.
-
D.
usedAsMarketingTitleIn
chosen
Indicates that something serves as a marketing title or promotional label within a specified context or medium.
-
E.
isFamouslyUsedIn
Indicates that something is widely recognized or well-known for being used in a particular context, work, or situation.
- 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_69e25d20156c81908c5c53195bd9c738 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f197efd98c819083635a2b8440f3eb |
completed | April 29, 2026, 5:32 a.m. |
| PD | Predicate disambiguation | batch_69effcf8ca2c8190887d4f4656617d21 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 17, 2026, 5:16 p.m.