Triple
T16402178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Name Is |
E398326
|
entity |
| Predicate | parodiesCelebrities |
P43127
|
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: [My Name Is, parodiesCelebrities, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parodiesCelebrities Context triple: [My Name Is, parodiesCelebrities, true]
-
A.
parodies
Indicates that one entity imitates another in an exaggerated or humorous way, often to criticize or comment on the original.
-
B.
hasHumorousTreatmentOf
chosen
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
-
C.
notablePrankTarget
Indicates that the subject is a well-known or frequent target of pranks carried out by the object.
-
D.
isHumorousCharacter
Indicates that the character is portrayed in a humorous way or primarily serves a comedic role in the context.
-
E.
cameoCharacter
Indicates that one entity appears briefly or in a minor, special-guest role within the context or work 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327d0652081908f42f78b156f3ae7 |
completed | April 18, 2026, 6:42 a.m. |
| PD | Predicate disambiguation | batch_69e226fe1dd08190865c181721f8c348 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:09 a.m.