Triple
T23619133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurzweil K2500 |
E583263
|
entity |
| Predicate | effectsProcessor |
P54676
|
FINISHED |
| Object | KDFX (optional) |
—
|
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: KDFX (optional) | Statement: [Kurzweil K2500, effectsProcessor, KDFX (optional)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectsProcessor Context triple: [Kurzweil K2500, effectsProcessor, KDFX (optional)]
-
A.
resolutionEffect
Indicates the outcome, consequence, or change that results from a particular resolution, decision, or problem-solving action.
-
B.
audioProcessing
chosen
Indicates that one entity performs operations to analyze, modify, or transform audio data associated with another entity.
-
C.
effectOnOutput
Indicates how one factor, action, or condition influences or changes the resulting output of a process or system.
-
D.
specialEffectsBy
Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or entity.
-
E.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
- 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_69e248fbcd9081908ba08913f9d30826 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b17780a88190b6f0d6d551133454 |
completed | April 29, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:45 p.m.