Triple
T2614728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pepé Le Pew |
E58859
|
entity |
| Predicate | hasParodyOf |
P10352
|
FINISHED |
| Object | French lover archetype |
—
|
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: French lover archetype | Statement: [Pepé Le Pew, hasParodyOf, French lover archetype]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParodyOf Context triple: [Pepé Le Pew, hasParodyOf, French lover archetype]
-
A.
parodies
chosen
Indicates that one entity imitates another in an exaggerated or humorous way, often to criticize or comment on the original.
-
B.
adaptedWorkOf
Indicates that one work is derived from, based on, or reinterprets the content of another pre-existing work.
-
C.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
D.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
-
E.
portraysFictionalEntity
Indicates that one entity depicts, represents, or plays the role of a fictional character or figure.
- 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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd89325308190985598373eb0d296 |
completed | March 7, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69abd80cd7fc81909e9696db2919129f |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.