Triple
T34566962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish Riding School of Vienna |
E887516
|
entity |
| Predicate | hasMusicAccompaniment |
P184079
|
FINISHED |
| Object | classical music |
—
|
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: classical music | Statement: [Spanish Riding School of Vienna, hasMusicAccompaniment, classical music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMusicAccompaniment Context triple: [Spanish Riding School of Vienna, hasMusicAccompaniment, classical music]
-
A.
hasPianoAccompaniment
Indicates that something (such as a musical work or performance) is accompanied by a piano part.
-
B.
soundAccompaniment
chosen
Indicates that one entity’s occurrence, presence, or action is accompanied by a particular sound or set of sounds.
-
C.
hasNoInstrumentalAccompaniment
Indicates that an action or event occurs without any instrumental musical accompaniment.
-
D.
vocalAccompaniment
Indicates that one entity provides vocal support or accompaniment to another entity’s primary performance or action.
-
E.
hasMusical
Indicates that one entity features, includes, or is associated with a musical work, performance, or musical component.
- 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_69f349d1a5fc81908557a46875b2f157 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe0d165a48819098b854318a50d76c |
completed | May 8, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69fe0931002481908a95b34f95e9f64e |
completed | May 8, 2026, 4:02 p.m. |
Created at: May 1, 2026, 2:02 a.m.