Triple
T13573848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tico-Tico no Fubá |
E324231
|
entity |
| Predicate | melodicCharacteristics |
P9125
|
FINISHED |
| Object | virtuosic melody |
—
|
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: virtuosic melody | Statement: [Tico-Tico no Fubá, melodicCharacteristics, virtuosic melody]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: melodicCharacteristics Context triple: [Tico-Tico no Fubá, melodicCharacteristics, virtuosic melody]
-
A.
melodicContour
Indicates the pattern of pitch movement over time in a musical line, describing how notes rise, fall, or stay level relative to one another.
-
B.
melodicPattern
Indicates a recurring sequence of musical tones or intervals that forms a recognizable melodic structure within a piece.
-
C.
isMelodic
Indicates that something possesses a tuneful, harmonious, or musically pleasing quality.
-
D.
featuresCounterMelody
Indicates that the subject includes or incorporates a secondary melodic line that complements and contrasts with the main melody.
-
E.
notableSongCharacteristic
chosen
Indicates that a song is distinguished by a particular notable feature or quality, such as style, structure, or performance trait.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0106cb48190b20eb9bda131a68a |
completed | April 12, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.