Triple
T7288507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law & Order |
E163933
|
entity |
| Predicate | notableSoundEffect |
P22084
|
FINISHED |
| Object | "doink-doink" scene-change sound |
—
|
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: "doink-doink" scene-change sound | Statement: [Law & Order, notableSoundEffect, "doink-doink" scene-change sound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableSoundEffect Context triple: [Law & Order, notableSoundEffect, "doink-doink" scene-change sound]
-
A.
soundEffects
Indicates that one entity produces, contains, or is associated with sound effects used to accompany or enhance another entity.
-
B.
notableEffect
Indicates that one entity has a significant impact, consequence, or influence on another entity or situation.
-
C.
soundEngine
Indicates that one entity functions as or provides the sound engine (audio processing or synthesis system) used by another entity.
-
D.
hasSound
chosen
Indicates that an entity produces, emits, or is associated with a particular sound.
-
E.
notableGag
Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
- 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_69c6886093b88190a254b1ce6db8bae7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb6a73fc8190ae5ce81fd3e46d87 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76c5fbc8190b378830082f11cb0 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3 p.m.