Triple
T6349136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Nick Cannon Show |
E142823
|
entity |
| Predicate | featuresSegmentType |
P9638
|
FINISHED |
| Object | hidden camera sketches |
—
|
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: hidden camera sketches | Statement: [The Nick Cannon Show, featuresSegmentType, hidden camera sketches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresSegmentType Context triple: [The Nick Cannon Show, featuresSegmentType, hidden camera sketches]
-
A.
featuresSegment
Indicates that one entity includes or highlights a particular segment or portion of another entity as a notable part of it.
-
B.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
C.
featuresGroup
Indicates that an entity includes or is associated with a specific group as one of its features or components.
-
D.
typicalSegmentType
chosen
Indicates that something is classified as belonging to a usual or characteristic type of segment within a broader structure or sequence.
-
E.
featuresSample
Indicates that an entity includes or presents a particular sample as one of its components or examples.
- 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_69c008d6dcbc8190aa1c2f1fd8916b42 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067bba1988190b51f0a22e4279e1b |
completed | March 22, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69c060ea1a988190889e47b7e0c819b8 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:31 p.m.