Triple
T28326784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ushering in Banality |
E717429
|
entity |
| Predicate | stylisticDescriptor |
P48733
|
FINISHED |
| Object | kitsch‑inspired |
—
|
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: kitsch‑inspired | Statement: [Ushering in Banality, stylisticDescriptor, kitsch‑inspired]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stylisticDescriptor Context triple: [Ushering in Banality, stylisticDescriptor, kitsch‑inspired]
-
A.
stylisticElement
Indicates a relationship where one entity functions as a stylistic feature, device, or characteristic that shapes the expressive or aesthetic quality of another entity.
-
B.
styleDescribedAs
chosen
Indicates that the manner, aesthetic, or mode of something is characterized or labeled using a particular style description.
-
C.
stylisticFocus
Indicates a relationship where something is primarily concerned with, emphasizes, or is characterized by a particular style or set of stylistic features.
-
D.
stylisticEffect
Indicates the relationship where one element produces, contributes to, or embodies a particular stylistic impact or impression on another.
-
E.
stylisticRange
Indicates the range or spectrum of styles that characterize or can be applied to something.
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6493036f4819095f94ef6457dd35d |
completed | May 2, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 28, 2026, 12:29 a.m.