Triple
T8900395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fantasia on a Theme by Thomas Tallis |
E211914
|
entity |
| Predicate | inTuningSystem |
P65278
|
FINISHED |
| Object | tonal with modal harmony |
—
|
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: tonal with modal harmony | Statement: [Fantasia on a Theme by Thomas Tallis, inTuningSystem, tonal with modal harmony]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inTuningSystem Context triple: [Fantasia on a Theme by Thomas Tallis, inTuningSystem, tonal with modal harmony]
-
A.
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.
-
B.
usesMusicalSystem
chosen
Indicates that one entity employs or operates according to a particular musical system, framework, or set of musical rules.
-
C.
tonalCenter
Indicates that one musical element functions as the primary pitch or key center around which another musical element is organized.
-
D.
tuning
Indicates the adjustment or calibration of something’s parameters or settings to achieve desired performance or behavior.
-
E.
tuningMethod
Indicates the method or approach used to adjust or optimize something’s parameters or performance.
- 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_69ca83918d3081909b326fa3750cb8c8 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6428ffc48190814f6b865961dbd1 |
completed | April 1, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2bfb38819083d5eb1af8ccf4d6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:54 p.m.