Triple
T37224502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Luck Blackie |
E922969
|
entity |
| Predicate | featuresGagType |
P195489
|
FINISHED |
| Object | falling objects |
—
|
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: falling objects | Statement: [Bad Luck Blackie, featuresGagType, falling objects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresGagType Context triple: [Bad Luck Blackie, featuresGagType, falling objects]
-
A.
featuresRunningGag
Indicates that the subject includes or makes use of a recurring joke or humorous motif.
-
B.
couchGagType
Indicates the specific style or category of a recurring couch gag sequence associated with an entity.
-
C.
notableGag
Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
-
D.
gameFeatures
Indicates that a game includes or offers a particular element, characteristic, or functionality.
-
E.
featuresSlapstick
chosen
Indicates that the subject includes or prominently uses slapstick-style physical comedy in its content or presentation.
- 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_69f76ea7f0008190b31b8e30f3d05a71 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:15 p.m.