Triple
T22115073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chi vol haver felice e lieto il core |
E546518
|
entity |
| Predicate | vocalGenreContext |
P33180
|
FINISHED |
| Object | Italian madrigal tradition |
—
|
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: Italian madrigal tradition | Statement: [Chi vol haver felice e lieto il core, vocalGenreContext, Italian madrigal tradition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vocalGenreContext Context triple: [Chi vol haver felice e lieto il core, vocalGenreContext, Italian madrigal tradition]
-
A.
vocalGender
Indicates the perceived or assigned gender associated with an entity’s voice in a vocal performance or recording.
-
B.
hasMusicalVocalType
Indicates that an entity is associated with a specific type or classification of singing voice.
-
C.
genreContext
Indicates the contextual genre or categorical style associated with an entity, such as the thematic or stylistic framework in which it is situated.
-
D.
genreOfAssociatedPerson
Indicates that a particular genre is associated with a given person, such as an artist, author, or performer.
-
E.
styleOfMusic
chosen
Indicates the musical genre or stylistic category that characterizes a piece of music, artist, 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1294c5f908190bdb1cce3cbf86d85 |
completed | April 28, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69e71b2ed7348190b6fa2e52f54393fb |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:31 p.m.