Triple
T12815715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time Don’t Run Out on Me |
E306394
|
entity |
| Predicate | musicalArtistGenreOfPerformer |
P41449
|
FINISHED |
| Object | country pop |
—
|
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: country pop | Statement: [Time Don’t Run Out on Me, musicalArtistGenreOfPerformer, country pop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicalArtistGenreOfPerformer Context triple: [Time Don’t Run Out on Me, musicalArtistGenreOfPerformer, country pop]
-
A.
hasArtistGenre
Indicates that an artist is associated with or categorized under a particular musical or artistic genre.
-
B.
genreOfAssociatedPerson
chosen
Indicates that a particular genre is associated with a given person, such as an artist, author, or performer.
-
C.
hasGenreArtist
Indicates that an artist is associated with or specializes in a particular genre.
-
D.
hasMusicalArtistType
Indicates that an entity has a specific role or classification as a type of musical artist (e.g., solo artist, band, composer).
-
E.
musicalArtistAssociated
Indicates a relationship where one musical artist is professionally connected or affiliated with another, such as through collaboration, membership, or frequent association.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9beb30819097c256a5aab9a4c8 |
completed | April 10, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69d9640ed7448190b276e7fab649f7d2 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:31 p.m.