Triple
T3158456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Hagen as Lina Lamont |
E66045
|
entity |
| Predicate | usesPlotDevice |
P23847
|
FINISHED |
| Object | dubbingOfVoice |
—
|
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: dubbingOfVoice | Statement: [Jean Hagen as Lina Lamont, usesPlotDevice, dubbingOfVoice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPlotDevice Context triple: [Jean Hagen as Lina Lamont, usesPlotDevice, dubbingOfVoice]
-
A.
centralPlotDevice
Indicates that one entity functions as the main narrative mechanism or element around which the plot of the other entity is structured.
-
B.
hasNarrativeDevice
chosen
Indicates that one entity employs, contains, or is characterized by a particular narrative device used in storytelling or discourse.
-
C.
usedAgainst
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, another entity.
-
D.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
E.
toolUsed
Indicates that an action or task is performed using a particular tool as the means or instrument.
- 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_69ad85850c1481908a9e9c6242238de2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5ed82a08190a1bdcf18ee593c79 |
completed | March 8, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9dfbf0348190952a6bca8fc5fed1 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:05 p.m.