Triple
T10260922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theme from Mahogany (Do You Know Where You’re Going To) |
E240590
|
entity |
| Predicate | performedInGenre |
P83033
|
FINISHED |
| Object | adult contemporary |
—
|
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: adult contemporary | Statement: [Theme from Mahogany (Do You Know Where You’re Going To), performedInGenre, adult contemporary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: performedInGenre Context triple: [Theme from Mahogany (Do You Know Where You’re Going To), performedInGenre, adult contemporary]
-
A.
isInGenreOfArtistCareer
Indicates that an artist’s career belongs to or is categorized within a particular artistic genre.
-
B.
genreOfAssociatedPerson
Indicates that a particular genre is associated with a given person, such as an artist, author, or performer.
-
C.
usedGenre
chosen
Indicates that one entity employs or is associated with a particular genre in its creation, presentation, or classification.
-
D.
genreOfAppearance
Indicates the genre or type of creative work in which an entity appears.
-
E.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b5853081909cd0397e08a0f44d |
completed | April 7, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69d4d1edae6881909a65201b8e51ea0a |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:32 a.m.