Triple
T35186281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spike |
E1015990
|
entity |
| Predicate | humorRole |
P71317
|
FINISHED |
| Object | deadpan comic relief |
—
|
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: deadpan comic relief | Statement: [Spike, humorRole, deadpan comic relief]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: humorRole Context triple: [Spike, humorRole, deadpan comic relief]
-
A.
isHumorousCharacter
chosen
Indicates that the character is portrayed in a humorous way or primarily serves a comedic role in the context.
-
B.
roleInSatire
Indicates that an entity serves as a character, target, or contributing element within a satirical work or satirical context.
-
C.
humorSetting
Indicates a relationship where one entity specifies or controls the level, style, or presence of humor applied to another entity or context.
-
D.
humorousTone
Indicates that the related communication, expression, or interaction is characterized by humor, playfulness, or comedic intent.
-
E.
humourTarget
Indicates that one entity is the object or focus of another entity’s humor, such as jokes, teasing, or comedic commentary.
- 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_69f76ddd815c8190b822eea06630f9fb |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78dc26cc0819097f39a5d04037670 |
completed | May 3, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:02 p.m.