Triple
T20618496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Want to Be on TV |
E506632
|
entity |
| Predicate | hasSatiricalTone |
P140803
|
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: [I Want to Be on TV, hasSatiricalTone, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSatiricalTone Context triple: [I Want to Be on TV, hasSatiricalTone, true]
-
A.
hasNotableSatire
Indicates that one entity is recognized for containing or exemplifying a significant satirical treatment of the other entity.
-
B.
humorousTone
Indicates that the related communication, expression, or interaction is characterized by humor, playfulness, or comedic intent.
-
C.
isSatiricalCycleComponent
Indicates that something functions as a constituent part of a larger satirical cycle or series.
-
D.
hasHumorousTreatmentOf
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
-
E.
hasIronicMeaning
Indicates that something conveys a meaning opposite to or incongruent with its literal expression, creating an ironic effect.
- F. None of above. chosen
Provenance (4 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abdf9d7c8190969247a4ae55b781 |
completed | April 20, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69e5a00c43308190b7ea58d559257e07 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a9f3f88190b961db9aca36f7da |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:41 a.m.