Triple
T5434629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lullaby |
E121576
|
entity |
| Predicate | setToMusicIn |
P64042
|
FINISHED |
| Object | various song and choral settings by composers |
—
|
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: various song and choral settings by composers | Statement: [Lullaby, setToMusicIn, various song and choral settings by composers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setToMusicIn Context triple: [Lullaby, setToMusicIn, various song and choral settings by composers]
-
A.
settingInMusical
Indicates that one entity serves as the setting or location in which the events of a musical take place.
-
B.
setToMusicByYear
Indicates that something was set to music in a specific year.
-
C.
musicSource
Indicates that one entity serves as the origin or provider of music for another entity or context.
-
D.
musicFocus
Indicates that the primary attention or emphasis is directed toward music or musical aspects.
-
E.
musicalMode
Indicates the specific tonal framework or scale system (mode) in which a piece of music or musical passage is organized.
- F. None of above. chosen
Provenance (4 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_69bd463c65f0819082ee6483ab4b466a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd922f66bc8190b7d47fd68d2fcf2e |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd919aeb048190b786f814177d6cd9 |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd922dc688819092bf33589ebc6d50 |
completed | March 20, 2026, 6:30 p.m. |
Created at: March 20, 2026, 2:06 p.m.