Triple
T15920914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Day Breaks |
E386088
|
entity |
| Predicate | labelGenreAssociation |
P38924
|
FINISHED |
| Object | Blue Note jazz catalog |
—
|
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: Blue Note jazz catalog | Statement: [Day Breaks, labelGenreAssociation, Blue Note jazz catalog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelGenreAssociation Context triple: [Day Breaks, labelGenreAssociation, Blue Note jazz catalog]
-
A.
genreAssociatedWith
chosen
Indicates a relationship where a work, item, or entity is linked to or categorized under a particular genre.
-
B.
associatedWithGenreElement
Indicates that something has a connection or linkage to a specific genre-related element (such as a motif, convention, or stylistic feature).
-
C.
hasGenreOfClaim
Indicates that a claim is categorized or classified under a particular genre or type of claim.
-
D.
keyGenreFilm
Indicates that a particular genre is the primary or defining genre associated with a given film.
-
E.
associatedWithGenreScene
Indicates that an entity is connected or related to a particular genre scene, such as a specific stylistic or cultural subcommunity within a broader 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:52 a.m.