Triple
T29601292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Vargas |
E754452
|
entity |
| Predicate | involvedInPlotTheme |
P30025
|
FINISHED |
| Object | cross-border crime |
—
|
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: cross-border crime | Statement: [Susan Vargas, involvedInPlotTheme, cross-border crime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvedInPlotTheme Context triple: [Susan Vargas, involvedInPlotTheme, cross-border crime]
-
A.
plotInvolvement
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.
allegedPlots
Indicates that one entity is accused or suspected of planning or conspiring to carry out harmful or illicit actions involving another entity.
-
E.
themeInvolvingCharacter
chosen
Indicates that a theme, motif, or abstract concept centrally involves or is significantly shaped by a particular character.
- 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_69f0ef84e5d08190a0df17f5930ceed3 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: April 28, 2026, 6:22 p.m.