Triple
T16901745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F major |
E424453
|
entity |
| Predicate | numberOfAccidentals |
P125129
|
FINISHED |
| Object | 1 flat |
—
|
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: 1 flat | Statement: [F major, numberOfAccidentals, 1 flat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAccidentals Context triple: [F major, numberOfAccidentals, 1 flat]
-
A.
hasTuningDivision
Indicates that one entity specifies or uses a particular system or scheme for dividing a range (such as a musical interval or scale) into tuning units.
-
B.
musicTheoryContext
Indicates that one entity is interpreted or analyzed within the framework, rules, or concepts of music theory in relation to another entity or situation.
-
C.
numberOfFrets
Indicates the specific count of frets associated with an instrument or fretboard.
-
D.
hasKeySignatureDistribution
Indicates that there is a specific pattern or spread of key signatures associated with the entity, describing how frequently or prominently different key signatures occur.
-
E.
musicalSymbol
Indicates that one entity is a musical notation mark or sign associated with another entity in a musical context.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8dc7cf08190ad935935d8daf1d0 |
completed | April 18, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69e32b9489408190bcb2ede567ff5bf9 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:29 a.m.