Triple
T31655869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slap Bet |
E807856
|
entity |
| Predicate | runningGagIntroduced |
P52455
|
FINISHED |
| Object | Barney’s fear of being slapped |
—
|
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: Barney’s fear of being slapped | Statement: [Slap Bet, runningGagIntroduced, Barney’s fear of being slapped]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runningGagIntroduced Context triple: [Slap Bet, runningGagIntroduced, Barney’s fear of being slapped]
-
A.
notableGag
chosen
Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
-
B.
reasonForRunningGag
Indicates the underlying cause or explanation for why a particular running gag recurs.
-
C.
recurringCharacterIntroduced
Indicates that a character is introduced in a work as one who appears repeatedly across multiple episodes, issues, or installments.
-
D.
hasHumorousSubplotActor
Indicates that an actor participates in or is responsible for a humorous subplot within a larger work.
-
E.
introducedForSeries
Indicates that an entity was first created or brought into existence specifically for inclusion in a particular series.
- 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_69f348daf95c81908b4c985b7ddcd0b3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a95e38ac819096c03f2b9872260f |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a757c6e081908e37631e5d8d246b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 30, 2026, 10:55 p.m.