Triple
T37129706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ty Burrell as Mr. Peabody |
E919482
|
entity |
| Predicate | characterCatchphraseStyle |
P112889
|
FINISHED |
| Object | punBasedHumor |
—
|
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: punBasedHumor | Statement: [Ty Burrell as Mr. Peabody, characterCatchphraseStyle, punBasedHumor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterCatchphraseStyle Context triple: [Ty Burrell as Mr. Peabody, characterCatchphraseStyle, punBasedHumor]
-
A.
characterCatchphrase
Indicates that a particular phrase is commonly and distinctively used by a character as their catchphrase.
-
B.
hasCatchphraseStyle
chosen
Indicates that an entity’s catchphrase conforms to, or is characterized by, a particular stylistic pattern or manner of expression.
-
C.
hasCatchphraseText
Indicates that an entity is associated with a specific catchphrase expressed as text.
-
D.
hasCatchphraseElement
Indicates that one entity is a component, word, or segment that forms part of another entity’s catchphrase.
-
E.
featuresCatchphrase
Indicates that an entity prominently includes or is associated with a particular catchphrase.
- 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_69f76e9d13e48190a108f7fbf80ff375 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ffcc6182b48190afb598ced6500e66 |
completed | May 10, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69ffcbb363748190bc6f8d038fba44ff |
completed | May 10, 2026, 12:05 a.m. |
Created at: May 3, 2026, 4:15 p.m.