Triple
T29372138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OPM |
E744881
|
entity |
| Predicate | lfoSupport |
P166690
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [OPM, lfoSupport, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lfoSupport Context triple: [OPM, lfoSupport, yes]
-
A.
hasLFEChannels
Indicates that an entity includes or is associated with one or more Low-Frequency Effects (LFE) audio channels.
-
B.
supportsMIDI
Indicates that one entity provides compatibility with or the ability to use MIDI (Musical Instrument Digital Interface) functionality for another entity.
-
C.
supportsMultiTimbralOperation
Indicates that an entity can operate in a multi-timbral mode, handling multiple distinct timbres or instrument parts simultaneously.
-
D.
supportsAutoLowLatencyMode
Indicates that the subject is capable of automatically enabling and managing a low-latency mode for its operations or interactions.
-
E.
supportsFFTSize
Indicates that one entity is capable of operating with or accommodating a specified FFT (Fast Fourier Transform) size.
- 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_69f0a79ba954819094597628112c6091 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f669ab36008190bc2e3c5dbdd2050d |
completed | May 2, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f660f4f7a88190b93c60d76b86c912 |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f661b47d088190934f63884a203261 |
completed | May 2, 2026, 8:42 p.m. |
Created at: April 28, 2026, 2:28 p.m.