Triple
T20234407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Palm Beach Story |
E495610
|
entity |
| Predicate | followsTrope |
P68123
|
FINISHED |
| Object | marital mix-up |
—
|
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: marital mix-up | Statement: [The Palm Beach Story, followsTrope, marital mix-up]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsTrope Context triple: [The Palm Beach Story, followsTrope, marital mix-up]
-
A.
usedAsTrope
chosen
Indicates that something functions as a recurring narrative device, motif, or cliché within a story or set of stories.
-
B.
inspiredTrope
Indicates that one trope serves as the creative or conceptual inspiration for another trope.
-
C.
subvertsTrope
Indicates that one entity challenges, undermines, or reverses the expected pattern or convention represented by a particular trope.
-
D.
followsPlot
Indicates that one narrative element adheres to, continues, or is consistent with the storyline established by another.
-
E.
followsStoryOf
Indicates that one narrative, account, or storyline continues from, is based on, or is derived from the events or structure of another.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e67167fae88190a26ff10d698174f8 |
completed | April 20, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69e55b18609481909ab28bc8750a642f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:40 p.m.