Triple
T26758549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gwen Saunders |
E674735
|
entity |
| Predicate | involvedInPlotType |
P17462
|
FINISHED |
| Object | farcical plot |
—
|
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: farcical plot | Statement: [Gwen Saunders, involvedInPlotType, farcical plot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvedInPlotType Context triple: [Gwen Saunders, involvedInPlotType, farcical plot]
-
A.
plotInvolvement
chosen
Indicates that an entity participates in, contributes to, or is affected by the events or storyline of a narrative work.
-
B.
partOfPlot
Indicates that one event, action, or element is a constituent component within the overall plot of a narrative.
-
C.
hasPoliticalPlot
Indicates that the subject work contains a storyline or narrative element centered on politics, political events, or political power struggles.
-
D.
hasNotableTraitInPlot
Indicates that a character or entity possesses a distinctive trait that plays a significant role within the narrative or plot.
-
E.
hasBeenInvolvedIn
Indicates that an entity has participated in, taken part in, or been connected to a particular event, activity, or situation.
- 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6f8565134819096aac0175f924a9f |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
Created at: April 27, 2026, 3:56 a.m.