Triple
T16880219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No Sleep till Brooklyn |
E421395
|
entity |
| Predicate | hasParodyAndHomageIn |
P10352
|
FINISHED |
| Object | popular culture |
—
|
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: popular culture | Statement: [No Sleep till Brooklyn, hasParodyAndHomageIn, popular culture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParodyAndHomageIn Context triple: [No Sleep till Brooklyn, hasParodyAndHomageIn, popular culture]
-
A.
parodies
chosen
Indicates that one entity imitates another in an exaggerated or humorous way, often to criticize or comment on the original.
-
B.
hasHumorousTreatmentOf
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
-
C.
hasFictionalSong
Indicates that one entity includes, features, or is associated with a song that is fictional or exists only within a narrative context.
-
D.
hasCulturalReference
Indicates that one entity makes reference to, draws from, or is associated with the cultural content, symbols, or traditions represented by another entity.
-
E.
hasNotableSatire
Indicates that one entity is recognized for containing or exemplifying a significant satirical treatment of the other 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7fa96588190837777c401880cb3 |
completed | April 18, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:29 a.m.