Triple
T28377080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jungle Cruise (Disneyland attraction) |
E718780
|
entity |
| Predicate | notableJoke |
P52455
|
FINISHED |
| Object | back side of water 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: back side of water gag | Statement: [Jungle Cruise (Disneyland attraction), notableJoke, back side of water gag]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableJoke Context triple: [Jungle Cruise (Disneyland attraction), notableJoke, back side of water gag]
-
A.
notableGag
chosen
Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
-
B.
humorSource
Indicates that one entity is the origin or cause of humor experienced in relation to another entity.
-
C.
notableFact
Indicates that there exists a particularly significant or noteworthy fact or piece of information associated with the subject.
-
D.
notableRiddle
Indicates that an entity is a well-known or significant riddle associated with another entity (such as a person, work, or context).
-
E.
notableQuote
Indicates that one entity is a significant or well-known quotation attributed to, recorded by, or strongly associated with another entity.
- 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_6a00d15f7b788190a3bf440be7837192 |
completed | May 10, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_6a00d0f8ef548190b1c15b06164eec4a |
completed | May 10, 2026, 6:39 p.m. |
Created at: April 28, 2026, 1:03 a.m.