Triple
T38389244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonata for Two Pianos and Percussion |
E899662
|
entity |
| Predicate | numberOfPercussionPlayers |
P204634
|
FINISHED |
| Object | 2 |
—
|
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 | Statement: [Sonata for Two Pianos and Percussion, numberOfPercussionPlayers, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPercussionPlayers Context triple: [Sonata for Two Pianos and Percussion, numberOfPercussionPlayers, 2]
-
A.
numberOfMusicians
Indicates the quantity of musicians associated with a given entity or event.
-
B.
hasPowerfulPercussion
Indicates that an entity features or produces percussion that is notably strong, intense, or forceful in impact.
-
C.
percussionType
Indicates the specific kind or category of percussion instrument associated with an entity.
-
D.
hasApproximateNumberOfMusicians
Indicates that an entity is associated with an estimated or approximate count of musicians involved with it.
-
E.
percussion
Indicates that an entity produces sound by being struck, shaken, or otherwise hit, as in playing or functioning as a percussion instrument.
- F. None of above. chosen
Provenance (4 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_69f76e5c9b808190b486523f5c2f817d |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:31 p.m.