Triple
T8770557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rapsodie espagnole |
E208447
|
entity |
| Predicate | usesRhythmType |
P7864
|
FINISHED |
| Object | habanera rhythm |
—
|
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: habanera rhythm | Statement: [Rapsodie espagnole, usesRhythmType, habanera rhythm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesRhythmType Context triple: [Rapsodie espagnole, usesRhythmType, habanera rhythm]
-
A.
hasRhythmicStyle
chosen
Indicates that one entity exhibits or is characterized by a particular rhythmic pattern or style in its expression or behavior.
-
B.
hasRhythmicOrigin
Indicates that something originates from, is derived from, or is fundamentally based on rhythm or rhythmic patterns.
-
C.
usesMusicalSystem
Indicates that one entity employs or operates according to a particular musical system, framework, or set of musical rules.
-
D.
hasRhythmOrigin
Indicates that one rhythm, style, or rhythmic pattern originates from, is derived from, or has its roots in another source.
-
E.
rhythmicOrganization
Indicates how temporal patterns, accents, and durations are structured or arranged in relation to one another within a sequence or system.
- 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_69ca835edb4481909b4aafb616dc5eb7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f2b08f881909f3d4fab2eda1d67 |
completed | March 31, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:41 p.m.