Triple
T11753142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beethoven piano sonatas |
E279455
|
entity |
| Predicate | movementCountRange |
P32659
|
FINISHED |
| Object | 2 to 4 movements per sonata |
—
|
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: 2 to 4 movements per sonata | Statement: [Beethoven piano sonatas, movementCountRange, 2 to 4 movements per sonata]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: movementCountRange Context triple: [Beethoven piano sonatas, movementCountRange, 2 to 4 movements per sonata]
-
A.
movementCount
Indicates the number of times a movement or relocation action has occurred between the related entities.
-
B.
movementNumber
Indicates the specific sequential position of a movement within a larger multi-movement work or performance.
-
C.
numberOfMovements
chosen
Indicates the total count of distinct movements or motion events associated with the given entity or context.
-
D.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
E.
mukhiCountRange
Indicates a constraint on the allowable minimum and/or maximum number of mukhis (faces/segments) associated with an 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a509c2448190b0deb7ed29c3a73f |
completed | April 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69d88a813cc48190a3dfdc60e8af80ae |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.