Triple
T34334881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fantazias for viols |
E881116
|
entity |
| Predicate | typicalNumberOfParts |
P190503
|
FINISHED |
| Object | 3 to 6 parts (approximate) |
—
|
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: 3 to 6 parts (approximate) | Statement: [Fantazias for viols, typicalNumberOfParts, 3 to 6 parts (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNumberOfParts Context triple: [Fantazias for viols, typicalNumberOfParts, 3 to 6 parts (approximate)]
-
A.
typicalNumberOfComponents
Indicates the usual or standard count of distinct components that an entity is expected to have.
-
B.
hasApproximateNumberOfPieces
chosen
Indicates that an entity is associated with an estimated or non-exact count of pieces or components.
-
C.
hasPartNumber
Indicates that one entity is assigned or associated with a specific part number used to identify it within a catalog, system, or inventory.
-
D.
numberOfPieces
Indicates the quantity of discrete parts or units into which something is divided or composed.
-
E.
typicalPackSize
Indicates the usual quantity of items contained together in a single package for that 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_69f349ba96a08190b94887bae2d8ee49 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:58 a.m.