Triple
T29028945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mit gutem Humor (No. 16) |
E737672
|
entity |
| Predicate | isMiniatureWithin |
P107378
|
FINISHED |
| Object | Davidsbündlertänze, Op. 6 |
—
|
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: Davidsbündlertänze, Op. 6 | Statement: [Mit gutem Humor (No. 16), isMiniatureWithin, Davidsbündlertänze, Op. 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMiniatureWithin Context triple: [Mit gutem Humor (No. 16), isMiniatureWithin, Davidsbündlertänze, Op. 6]
-
A.
hasMiniature
Indicates that one entity possesses or includes a smaller-scale representation or model of another entity.
-
B.
hasApproximateNumberOfMiniatures
Indicates that an entity is associated with an estimated or non-exact count of miniatures.
-
C.
isMinorFigureIn
Indicates that an entity plays a small, secondary, or relatively insignificant role within another entity, such as a work, event, or context.
-
D.
miniaturizedIn
chosen
Indicates that one entity exists as a smaller-scale or reduced-size version within or relative to another entity.
-
E.
isSmall
Indicates that one entity has a size that is relatively small, either in absolute terms or compared to a reference standard or another entity.
- 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6600bfbf081909eb61c47571e0277 |
completed | May 2, 2026, 8:35 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 9:54 a.m.