Triple
T23246733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyrie–Gloria–Credo–Sanctus–Agnus Dei |
E581601
|
entity |
| Predicate | musicallySetBy |
P19883
|
FINISHED |
| Object | Giovanni Pierluigi da Palestrina |
—
|
NE NERFINISHED |
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: Giovanni Pierluigi da Palestrina | Statement: [Kyrie–Gloria–Credo–Sanctus–Agnus Dei, musicallySetBy, Giovanni Pierluigi da Palestrina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicallySetBy Context triple: [Kyrie–Gloria–Credo–Sanctus–Agnus Dei, musicallySetBy, Giovanni Pierluigi da Palestrina]
-
A.
setToMusicAs
Indicates that one entity (typically a text or work) has been adapted and arranged by another entity into a musical composition.
-
B.
settingInMusical
Indicates that one entity serves as the setting or location in which the events of a musical take place.
-
C.
musicOrchestratedBy
Indicates that a piece of music or musical work is arranged or orchestrated by a specific person or entity.
-
D.
hasMusicalSettingsBy
chosen
Indicates that a work has been set to music or musically arranged by a specified creator or composer.
-
E.
hasMusicalArrangementCharacteristic
Indicates that a musical arrangement possesses a specific characteristic, feature, or quality.
- 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f1e8448190b8420a8dc6e24576 |
completed | April 29, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:10 p.m.