Triple
T25801106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NHK General TV |
E649830
|
entity |
| Predicate | genreMix |
P2561
|
FINISHED |
| Object | multi-genre channel |
—
|
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: multi-genre channel | Statement: [NHK General TV, genreMix, multi-genre channel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreMix Context triple: [NHK General TV, genreMix, multi-genre channel]
-
A.
genreIncludes
Indicates that a broader genre category encompasses or contains a specified subgenre or work as part of its classification.
-
B.
genreDiversity
chosen
Indicates the extent to which an entity involves, includes, or spans multiple distinct genres rather than being confined to a single genre.
-
C.
musicGenreCategory
Indicates that one entity is a broader music genre category under which the other music genre is classified.
-
D.
commercialMix
Indicates a relationship where different commercial elements, such as products, services, or marketing components, are combined or integrated into a single offering or context.
-
E.
genreTrend
Indicates how the popularity or prevalence of a particular genre changes over time or across contexts.
- 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_69e7ab34f8c8819099f6c4dabdabf129 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 22, 2026, 6:38 a.m.