Triple
T8348794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hymn Tune Prelude on ‘Song 13’ |
E196105
|
entity |
| Predicate | usesHarmonyStyle |
P30520
|
FINISHED |
| Object | late-Romantic |
—
|
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: late-Romantic | Statement: [Hymn Tune Prelude on ‘Song 13’, usesHarmonyStyle, late-Romantic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesHarmonyStyle Context triple: [Hymn Tune Prelude on ‘Song 13’, usesHarmonyStyle, late-Romantic]
-
A.
usesHarmony
Indicates that one entity employs or incorporates harmony—such as coordinated or consonant combinations of elements—in relation to another entity or context.
-
B.
hasHarmony
Indicates that two or more entities are in a state of balance, agreement, or pleasing coordination with one another.
-
C.
usesHarmonics
Indicates that one entity employs harmonic frequencies or overtones of another entity or signal as part of its operation or behavior.
-
D.
usesAsStyleOf
chosen
Indicates that one entity adopts or applies another entity as a stylistic model, method, or manner of expression.
-
E.
hasStyle
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
- 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_69ca82edd63c8190b876b8465464c5fa |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb8016c4188190a5ff93078e74dc39 |
completed | March 31, 2026, 8:04 a.m. |
| PD | Predicate disambiguation | batch_69cb70c6d0ec8190acf273b0e007b51a |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:58 p.m.