Triple
T21560290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronnie Fish |
E531996
|
entity |
| Predicate | hasComedicMisadventures |
P45834
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ronnie Fish, hasComedicMisadventures, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComedicMisadventures Context triple: [Ronnie Fish, hasComedicMisadventures, true]
-
A.
hasComedyElements
chosen
Indicates that something contains humorous or comedic aspects as part of its overall content or style.
-
B.
hasComedyAlbum
Indicates that one entity possesses, has released, or is associated with a comedy album.
-
C.
Prank Encounters
Indicates a relationship where one party orchestrates a deceptive or surprising prank scenario that another party unexpectedly experiences or becomes the target of.
-
D.
comedicDynamicWith
Indicates a relationship in which two or more entities interact in a way that creates or supports comedic effect, timing, or contrast.
-
E.
hasHumorousTreatmentOf
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
- 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_69e0c460232c81908de2c3819d17c00e |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eed2e2db2c81908b965312c50d4354 |
completed | April 27, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69e6320c8c2c81908bf031447d66a052 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:29 p.m.