Triple
T23480674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lloyd Bridges as Steve McCroskey |
E570395
|
entity |
| Predicate | runningGagPhrase |
P74838
|
FINISHED |
| Object | I picked the wrong week to quit smoking. |
—
|
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: I picked the wrong week to quit smoking. | Statement: [Lloyd Bridges as Steve McCroskey, runningGagPhrase, I picked the wrong week to quit smoking.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runningGagPhrase Context triple: [Lloyd Bridges as Steve McCroskey, runningGagPhrase, I picked the wrong week to quit smoking.]
-
A.
typicalPhrase
Indicates that the object is a phrase commonly or characteristically used in connection with the subject.
-
B.
notableGag
Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
-
C.
reasonForRunningGag
Indicates the underlying cause or explanation for why a particular running gag recurs.
-
D.
humorSource
Indicates that one entity is the origin or cause of humor experienced in relation to another entity.
-
E.
characterCatchphrase
chosen
Indicates that a particular phrase is commonly and distinctively used by a character as their catchphrase.
- 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_69f1a75002008190b02fbffd94e5e8b1 |
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.