Triple
T7775436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Mabuse the Gambler |
E221378
|
entity |
| Predicate | usesPlotElement |
P2762
|
FINISHED |
| Object | hypnosis |
—
|
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: hypnosis | Statement: [Dr. Mabuse the Gambler, usesPlotElement, hypnosis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPlotElement Context triple: [Dr. Mabuse the Gambler, usesPlotElement, hypnosis]
-
A.
plotElement
chosen
Indicates that one entity functions as a narrative component or structural element within the storyline of another entity (such as a work of fiction or media).
-
B.
usesElement
Indicates that one entity makes use of, incorporates, or depends on a specified element in its structure, function, or behavior.
-
C.
drivesPlotElement
Indicates that one element of the narrative is a primary cause or motivator for the development, progression, or outcome of another plot element.
-
D.
onChart
Indicates that one entity is visually represented or displayed on a chart associated with another entity.
-
E.
usesElementsOf
Indicates that one entity incorporates, applies, or draws upon components, principles, or features derived from another entity.
- 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_69ca83ebbef881909ac47f789145fef7 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cae7e779ec8190b77296d9c2ac3210 |
completed | March 30, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69caa488532c819093ac40bba0b3c7ef |
completed | March 30, 2026, 4:27 p.m. |
Created at: March 30, 2026, 3:45 p.m.