Triple
T11760211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mac and Me |
E279633
|
entity |
| Predicate | usedAsRunningGag |
P68123
|
FINISHED |
| Object | Paul Rudd’s talk show appearances |
—
|
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: Paul Rudd’s talk show appearances | Statement: [Mac and Me, usedAsRunningGag, Paul Rudd’s talk show appearances]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsRunningGag Context triple: [Mac and Me, usedAsRunningGag, Paul Rudd’s talk show appearances]
-
A.
usedAsTrope
chosen
Indicates that something functions as a recurring narrative device, motif, or cliché within a story or set of stories.
-
B.
notableGag
Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
-
C.
parodies
Indicates that one entity imitates another in an exaggerated or humorous way, often to criticize or comment on the original.
-
D.
humorSetting
Indicates a relationship where one entity specifies or controls the level, style, or presence of humor applied to another entity or context.
-
E.
hasHumorousTreatmentOf
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a52386708190b744746a2db37495 |
completed | April 10, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69d88a829fe481909cc5431de7d6058e |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.