Triple
T6067075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob's Burgers |
E135185
|
entity |
| Predicate | hasOpeningGagType |
P45798
|
FINISHED |
| Object | storefront gag |
—
|
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: storefront gag | Statement: [Bob's Burgers, hasOpeningGagType, storefront gag]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpeningGagType Context triple: [Bob's Burgers, hasOpeningGagType, storefront gag]
-
A.
hasHumorType
Indicates that an entity possesses or is characterized by a particular style, category, or type of humor.
-
B.
hasComedyElements
Indicates that something contains humorous or comedic aspects as part of its overall content or style.
-
C.
notableGag
Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
-
D.
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).
-
E.
hasOpeningFeature
chosen
Indicates that an entity possesses a specific characteristic, element, or attribute related to its opening or entry point.
- 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_69c00879e8048190b690717d19c5bc03 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0573f17088190a728f1c290cc9d1d |
completed | March 22, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69c049f031408190b08b2766237c5dd0 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:10 p.m.