Triple
T20347065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Values |
E495898
|
entity |
| Predicate | musicStyleShiftToward |
P139778
|
FINISHED |
| Object | tighter, more controlled arrangements |
—
|
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: tighter, more controlled arrangements | Statement: [New Values, musicStyleShiftToward, tighter, more controlled arrangements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicStyleShiftToward Context triple: [New Values, musicStyleShiftToward, tighter, more controlled arrangements]
-
A.
styleOfMusic
Indicates the musical genre or stylistic category that characterizes a piece of music, artist, or performance.
-
B.
musicMotif
Indicates a recurring musical idea, theme, or pattern that appears multiple times within a composition or across related works.
-
C.
genreTrend
Indicates how the popularity or prevalence of a particular genre changes over time or across contexts.
-
D.
genreShift
Indicates a change in the type or style of content, such as switching from one genre to another within a work or between works.
-
E.
mainGenreShiftTo
Indicates a change in the primary genre classification of something from one main genre to another.
- F. None of above. chosen
Provenance (4 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_69e0b4a3320881909495ae8bc30bc2dc |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67839e7b48190876ce7133a20c65b |
completed | April 20, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69e57636b4808190bc2855af48a3ccdc |
completed | April 20, 2026, 12:41 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:24 a.m.