Triple
T38093004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Desmond |
E951162
|
entity |
| Predicate | isPartOfPlot |
P103369
|
FINISHED |
| Object | sinister plot involving mind control |
—
|
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: sinister plot involving mind control | Statement: [Desmond, isPartOfPlot, sinister plot involving mind control]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartOfPlot Context triple: [Desmond, isPartOfPlot, sinister plot involving mind control]
-
A.
partOfPlot
chosen
Indicates that one event, action, or element is a constituent component within the overall plot of a narrative.
-
B.
usedInPlot
Indicates that something (e.g., an object, idea, or element) is employed as a component or device within the storyline or narrative structure of a plot.
-
C.
settingInPlot
Indicates that a particular setting or location serves as the backdrop or environment in which the events of a plot take place.
-
D.
plotInvolvement
Indicates that an entity participates in, contributes to, or is affected by the events or storyline of a narrative work.
-
E.
hasPoliticalPlot
Indicates that the subject work contains a storyline or narrative element centered on politics, political events, or political power struggles.
- 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_69f76f04960c8190a83f14ae4c67f5bc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a00262d71488190a769783fb09e5803 |
completed | May 10, 2026, 6:31 a.m. |
| PD | Predicate disambiguation | batch_6a0023985f148190a335a3fb93e9981e |
completed | May 10, 2026, 6:20 a.m. |
Created at: May 3, 2026, 4:21 p.m.