Triple
T7727072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gibson F-5 style mandolin |
E175156
|
entity |
| Predicate | hasPrimaryUseGenre |
P51264
|
FINISHED |
| Object | bluegrass 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: bluegrass music | Statement: [Gibson F-5 style mandolin, hasPrimaryUseGenre, bluegrass music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryUseGenre Context triple: [Gibson F-5 style mandolin, hasPrimaryUseGenre, bluegrass music]
-
A.
hasMainGenre
chosen
Indicates that an entity’s primary or most characteristic genre is the specified genre.
-
B.
hasNotableGenre
Indicates that an entity is significantly associated with a particular genre, such that the genre is especially characteristic or noteworthy for that entity.
-
C.
hasCanonicalGenre
Indicates that an entity is associated with its primary or officially recognized genre classification.
-
D.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
E.
hasSourceMaterialGenre
Indicates that the genre of the source material from which something is derived is specified.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:06 p.m.