Triple
T23480279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted Striker |
E570384
|
entity |
| Predicate | usesRunningGag |
P94189
|
FINISHED |
| Object | drinking problem |
—
|
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: drinking problem | Statement: [Ted Striker, usesRunningGag, drinking problem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesRunningGag Context triple: [Ted Striker, usesRunningGag, drinking problem]
-
A.
featuresRunningGag
Indicates that the subject includes or makes use of a recurring joke or humorous motif.
-
B.
hasRecurringGag
chosen
Indicates that a particular joke, situation, or comedic element repeatedly appears in relation to an entity (such as a character, series, or work).
-
C.
reasonForRunningGag
Indicates the underlying cause or explanation for why a particular running gag recurs.
-
D.
notableGag
Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
-
E.
canIncludeGagOrder
Indicates that a legal order or agreement has the authority to contain a provision restricting parties from publicly disclosing certain information (a gag order).
- 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_69e245af8a88819084f2704f6d265a92 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a74f48d8819080e875aaea8b46b3 |
completed | April 29, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69f0620ac3608190b36916261ea50f54 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 6:03 p.m.