Triple
T23858908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Are We Not Men? We Are Diva! |
E592386
|
entity |
| Predicate | hasHumorousStyle |
P14479
|
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: [Are We Not Men? We Are Diva!, hasHumorousStyle, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHumorousStyle Context triple: [Are We Not Men? We Are Diva!, hasHumorousStyle, true]
-
A.
hasHumorType
chosen
Indicates that an entity possesses or is characterized by a particular style, category, or type of humor.
-
B.
hasSatiricalTone
Indicates that something expresses its content in a mocking, ironic, or humorous way to criticize or ridicule its subject.
-
C.
hasComicStyle
Indicates that one entity is characterized by, presented in, or associated with a particular comic or cartoon-like visual style defined by the other entity.
-
D.
hasDramaticStyle
Indicates that an entity employs or is characterized by a theatrical, emotionally intense, or striking manner of expression or presentation.
-
E.
humorousTone
Indicates that the related communication, expression, or interaction is characterized by humor, playfulness, or comedic intent.
- 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_69e25d22eb488190914b193aff952e83 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c98cad34819080baeb8f20f39741 |
completed | April 29, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:12 p.m.