Triple
T10466385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Will McKenzie |
E246806
|
entity |
| Predicate | comedicFunction |
P43839
|
FINISHED |
| Object | source of cringe comedy |
—
|
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: source of cringe comedy | Statement: [Will McKenzie, comedicFunction, source of cringe comedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: comedicFunction Context triple: [Will McKenzie, comedicFunction, source of cringe comedy]
-
A.
comicFunction
chosen
Indicates a relationship where something serves a humorous or entertainment role, such as providing comedy, comic relief, or a joking purpose within a context.
-
B.
humorSetting
Indicates a relationship where one entity specifies or controls the level, style, or presence of humor applied to another entity or context.
-
C.
hasComedyElements
Indicates that something contains humorous or comedic aspects as part of its overall content or style.
-
D.
dramaticFunction
Indicates the role or purpose that something serves within the structure or progression of a dramatic work or narrative.
-
E.
humorSource
Indicates that one entity is the origin or cause of humor experienced in relation to another entity.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5092d6d408190b6bda4d7ced4601e |
completed | April 7, 2026, 1:39 p.m. |
| PD | Predicate disambiguation | batch_69d4fb84bafc8190819757b93620508a |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:19 p.m.