Triple
T29789939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E major |
E756375
|
entity |
| Predicate | keySignatureSharps |
P125129
|
FINISHED |
| Object | F# |
—
|
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: F# | Statement: [E major, keySignatureSharps, F#]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: keySignatureSharps Context triple: [E major, keySignatureSharps, F#]
-
A.
numberOfAccidentals
chosen
Indicates the relationship that specifies how many accidentals (sharps, flats, or naturals) are associated with a given musical element.
-
B.
hasKeySignature
Indicates that one musical work, passage, or notation is associated with a specific key signature defining its set of sharps or flats.
-
C.
supertonicKey
Indicates that one musical key stands in the supertonic (second scale degree) relationship to another key.
-
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.
scherzoKey
Indicates the musical key in which the scherzo section of a composition is written.
- 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_69f22451fb748190bbdbab401280affb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f674e1f0dc8190a9663a93706267b5 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 29, 2026, 5:12 p.m.