Triple
T7493267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uncommon Ritual |
E177058
|
entity |
| Predicate | featuresGenreFusion |
P14839
|
FINISHED |
| Object | fusion of bluegrass and classical music |
—
|
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: fusion of bluegrass and classical music | Statement: [Uncommon Ritual, featuresGenreFusion, fusion of bluegrass and classical music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresGenreFusion Context triple: [Uncommon Ritual, featuresGenreFusion, fusion of bluegrass and classical music]
-
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.
genreFeatures
Indicates that a particular genre is characterized or defined by certain features or attributes.
-
C.
genreDiversity
Indicates the extent to which an entity involves, includes, or spans multiple distinct genres rather than being confined to a single genre.
-
D.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
-
E.
commonGenre
Indicates that two entities share at least one genre in common.
- 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_69c69f2583808190bd1a4936c42a5815 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f81b431481908214b69c6c8d83bc |
completed | March 27, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d266d88190982cf5d2ee2e9564 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:43 p.m.