Triple
T23828590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gypsy Queen (Santana arrangement) |
E589451
|
entity |
| Predicate | originalComposerGenre |
P107782
|
FINISHED |
| Object | jazz |
—
|
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: jazz | Statement: [Gypsy Queen (Santana arrangement), originalComposerGenre, jazz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalComposerGenre Context triple: [Gypsy Queen (Santana arrangement), originalComposerGenre, jazz]
-
A.
hasGenreAsComposer
chosen
Indicates that an entity, in its role as a composer, is associated with a specific musical or artistic genre.
-
B.
originalPerformerGenre
Indicates that a performer is originally associated with or primarily known for a particular musical or artistic genre.
-
C.
favoriteComposer
Indicates that one entity is the preferred or most liked composer of another entity.
-
D.
hasMusicalComposer
Indicates that one entity serves as the musical composer responsible for creating the music associated with another entity.
-
E.
creatorRoleOfComposer
Indicates that an entity serves in the role of composer as the creator of 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_69e25d1922d481909cab567c06a802ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c7f304f08190bd965df06f013b3f |
completed | April 29, 2026, 8:57 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 8 p.m.