Triple
T21249757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FWV 48 |
E523710
|
entity |
| Predicate | workLanguageOfTempoMarkings |
P83111
|
FINISHED |
| Object | Italian |
—
|
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 | Statement: [FWV 48, workLanguageOfTempoMarkings, Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workLanguageOfTempoMarkings Context triple: [FWV 48, workLanguageOfTempoMarkings, Italian]
-
A.
languageOfTempoMarkings
chosen
Indicates the language in which the tempo markings of a musical work or score are written.
-
B.
movement3TempoMarking
Indicates the tempo marking associated specifically with the third movement of a musical work.
-
C.
languageOfMusicalTerms
Indicates the language in which specific musical terms are expressed or defined.
-
D.
hasTempoMarking
Indicates that a musical passage, piece, or event is associated with a specific tempo indication or marking.
-
E.
languageOfMusic
Indicates that a specified language is used in, associated with, or characteristic of a particular piece of music or musical work.
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7359c7a648190b4345336ac3be024 |
completed | April 21, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69e5f61239708190ab7b3c83ae848a0d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:56 p.m.