Triple
T4603532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Devil Without a Cause |
E100374
|
entity |
| Predicate | mainGenreFusion |
P14839
|
FINISHED |
| Object | rap, rock, and country |
—
|
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: rap, rock, and country | Statement: [Devil Without a Cause, mainGenreFusion, rap, rock, and country]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainGenreFusion Context triple: [Devil Without a Cause, mainGenreFusion, rap, rock, and country]
-
A.
musicFusionOf
chosen
Indicates a relationship where one musical work, style, or element is created by combining or blending two or more distinct musical sources or genres.
-
B.
genreDiversity
Indicates the extent to which an entity involves, includes, or spans multiple distinct genres rather than being confined to a single genre.
-
C.
commonGenre
Indicates that two entities share at least one genre in common.
-
D.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
E.
musicGenreBroad
Indicates that one music genre is a broader, more general category that encompasses another, more specific music genre.
- 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_69bd43cbc014819098b45f435908f88a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5975ec688190839bd22669343a76 |
completed | March 20, 2026, 2:28 p.m. |
| PD | Predicate disambiguation | batch_69bd522c811c81909aae4feadae33174 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:11 p.m.