Triple
T10070568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susie Myerson |
E213611
|
entity |
| Predicate | isCentralToPlotline |
P53895
|
FINISHED |
| Object | Midge Maisel’s stand-up comedy career |
—
|
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: Midge Maisel’s stand-up comedy career | Statement: [Susie Myerson, isCentralToPlotline, Midge Maisel’s stand-up comedy career]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCentralToPlotline Context triple: [Susie Myerson, isCentralToPlotline, Midge Maisel’s stand-up comedy career]
-
A.
isCentralTo
Indicates that something plays a primary, essential, or defining role in relation to something else, such that the latter depends on or is organized around it.
-
B.
hasMainPlotElement
chosen
Indicates that one entity serves as a central or primary plot element within the narrative of another entity.
-
C.
hasCentralFigure
Indicates that something features a primary or most important figure at its core or focus.
-
D.
isCentralAntagonist
Indicates that an entity serves as the primary opposing force or main villain driving conflict against the protagonist or central characters.
-
E.
isNarrativeDriven
Indicates that an entity’s primary structure or progression is guided by a storyline or plot rather than by mechanics, data, or other non-story elements.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcffa045c8190a08db0bb74cb006a |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b92573481909389bc6148ae7ea8 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:59 p.m.