Triple
T30142612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Audi RS models |
E766167
|
entity |
| Predicate | badgeLanguage |
P5036
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [Audi RS models, badgeLanguage, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: badgeLanguage Context triple: [Audi RS models, badgeLanguage, German]
-
A.
emblemLanguage
chosen
Indicates that an emblem (such as a symbol or logo) is associated with or presented in a particular language.
-
B.
labelNameLanguage
Indicates the language in which a given label or name is expressed.
-
C.
labelLanguageVariant
Indicates that one label is a language-specific variant or localized form of another label.
-
D.
brandLanguageVariant
Indicates that one language variant of a brand is related to or derived from another language version of the same brand.
-
E.
suffixLanguage
Indicates that one language is used as a suffix or ending element in the formation or representation of another language or linguistic expression.
- 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_69f2247909048190ae86c2160cf8b566 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67e8982648190b6bfb6b7f8b09d73 |
completed | May 2, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69f675ff62c48190a634bbb8896973b9 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:18 p.m.