Triple
T1886284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Škoda |
E39971
|
entity |
| Predicate | brandNameScript |
P14764
|
FINISHED |
| Object | Latin alphabet |
—
|
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: Latin alphabet | Statement: [Škoda, brandNameScript, Latin alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandNameScript Context triple: [Škoda, brandNameScript, Latin alphabet]
-
A.
brandNameDerivedFrom
Indicates that the brand’s name is derived from, based on, or taken from another specified name or source.
-
B.
brandingFeature
chosen
Indicates that one entity serves as a branding-related characteristic, element, or attribute that helps define or distinguish another entity’s brand identity.
-
C.
brand
Indicates that one entity is the commercial brand or label under which another entity (such as a product, service, or organization) is marketed or identified.
-
D.
hasBranding
Indicates that one entity carries, displays, or is associated with the brand identity of another entity.
-
E.
marketingNameOf
Indicates that one entity is the marketing or brand name used to promote or refer to another entity.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb12032c881909cd93e3601906f48 |
completed | March 7, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69abafe61bc48190ac9ead027df930e1 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.