Triple
T29660899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frame by Frame |
E750400
|
entity |
| Predicate | featuresMusicalTechnique |
P147037
|
FINISHED |
| Object | interlocking guitar parts |
—
|
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: interlocking guitar parts | Statement: [Frame by Frame, featuresMusicalTechnique, interlocking guitar parts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresMusicalTechnique Context triple: [Frame by Frame, featuresMusicalTechnique, interlocking guitar parts]
-
A.
musicalTechniques
chosen
Indicates the specific methods or approaches used to create, shape, or perform music in relation to an entity.
-
B.
notableInstrumentTechnique
Indicates that an entity is particularly recognized for using, developing, or being associated with a specific musical instrument technique.
-
C.
featuresTechnique
Indicates that something incorporates or makes use of a particular technique as part of its content or execution.
-
D.
musicalAbility
Indicates that an entity possesses skill, talent, or proficiency in performing, creating, or understanding music.
-
E.
featuresRichHarmonies
Indicates that the subject contains or employs complex, layered, and sonically dense harmonic structures.
- 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_69f0d6226fe881908819197c9ef9ee04 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69ff878f41888190bcb3bc41ad26081a |
completed | May 9, 2026, 7:14 p.m. |
| PD | Predicate disambiguation | batch_69ff854082d88190aad3bfedf05e849f |
completed | May 9, 2026, 7:04 p.m. |
Created at: April 28, 2026, 6:58 p.m.