Triple
T29984077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Toffer’s Book of Consequential Dogs |
E761679
|
entity |
| Predicate | hasParodicElement |
P10352
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Old Toffer’s Book of Consequential Dogs, hasParodicElement, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParodicElement Context triple: [Old Toffer’s Book of Consequential Dogs, hasParodicElement, yes]
-
A.
hasComedyElements
Indicates that something contains humorous or comedic aspects as part of its overall content or style.
-
B.
parodies
chosen
Indicates that one entity imitates another in an exaggerated or humorous way, often to criticize or comment on the original.
-
C.
hasAbsurdistElements
Indicates that something contains qualities, themes, or features characteristic of absurdism, such as illogical situations, irrational behavior, or a sense of meaninglessness.
-
D.
hasHumorousSubplotActor
Indicates that an actor participates in or is responsible for a humorous subplot within a larger work.
-
E.
meterParodied
Indicates that one metrical pattern or structure is used in a way that humorously imitates or mocks another metrical pattern.
- 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_69f2246851148190b8e76206db94b105 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fdd92396788190ae1424bc1ae55844 |
completed | May 8, 2026, 12:37 p.m. |
| PD | Predicate disambiguation | batch_69fdd678f40481909a717a2daec83b36 |
completed | May 8, 2026, 12:26 p.m. |
Created at: April 29, 2026, 6:36 p.m.