Triple
T21018947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiss FM |
E517751
|
entity |
| Predicate | hasLocalVariants |
P32680
|
FINISHED |
| Object | multiple local Kiss FM stations worldwide |
—
|
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: multiple local Kiss FM stations worldwide | Statement: [Kiss FM, hasLocalVariants, multiple local Kiss FM stations worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalVariants Context triple: [Kiss FM, hasLocalVariants, multiple local Kiss FM stations worldwide]
-
A.
hasRegionalVariationsIn
chosen
Indicates that something exhibits different forms, versions, or characteristics depending on the geographic region.
-
B.
usesLocalLanguageVariant
Indicates that an entity employs a region-specific or localized form of a language rather than a standard or global variant.
-
C.
languageVariants
Indicates that one language form is a variant or alternative version of another language.
-
D.
hasLinguisticVariety
Indicates that one entity possesses or exhibits a particular linguistic variety in relation to another entity or context.
-
E.
hasVariantsIn
Indicates that an entity exists in multiple alternative forms or versions within a specified context or set.
- 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_69e0b50262b081909bc488937145eb73 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc5b6af4819081fd3aa5212f17a5 |
completed | April 21, 2026, 4:26 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf274ac81909bbf245627dc8fdc |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 1:54 p.m.