Triple
T38238007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ed Wynn as Albert Dussell |
E1013675
|
entity |
| Predicate | portraysFate |
P180515
|
FINISHED |
| Object | deportation to Nazi concentration camps |
—
|
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: deportation to Nazi concentration camps | Statement: [Ed Wynn as Albert Dussell, portraysFate, deportation to Nazi concentration camps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysFate Context triple: [Ed Wynn as Albert Dussell, portraysFate, deportation to Nazi concentration camps]
-
A.
fateReflects
Indicates that one entity’s fate or outcome mirrors, parallels, or symbolically represents the fate or outcome of another entity.
-
B.
eventualFate
Indicates the ultimate outcome or final state that an entity is destined to reach over time.
-
C.
fate
Indicates that an entity is destined or predetermined to experience a particular outcome or course of events beyond its control.
-
D.
viewOnFate
Indicates a relationship where one entity holds a particular belief, attitude, or perspective about fate or predestination.
-
E.
hasFateInStory
chosen
Indicates that an entity is assigned a particular destiny, outcome, or ultimate role within the narrative of a story.
- 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_69f76dd72a248190a5fe18db2bd1eb15 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffc1550cb481908628e446d9b67f7b |
completed | May 9, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69ffc10a74708190ae90e2c378791f70 |
completed | May 9, 2026, 11:19 p.m. |
Created at: May 3, 2026, 4:30 p.m.