Triple
T3171667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Have Confidence |
E66360
|
entity |
| Predicate | filmSceneContext |
P7326
|
FINISHED |
| Object | Maria traveling to the von Trapp villa |
—
|
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: Maria traveling to the von Trapp villa | Statement: [I Have Confidence, filmSceneContext, Maria traveling to the von Trapp villa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmSceneContext Context triple: [I Have Confidence, filmSceneContext, Maria traveling to the von Trapp villa]
-
A.
filmingLocationContext
Indicates the contextual relationship specifying where the filming of an event, scene, or production took place.
-
B.
notableScene
chosen
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
C.
filmLocationFor
Indicates a relationship where a specific place serves as the filming location for a particular film or production.
-
D.
filmMovement
Indicates the cinematic movement or stylistic school with which a film is associated.
-
E.
performedInSceneType
Indicates that an action or event was carried out within a scene of a specified type or category.
- 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada66da23c81908f063b44b48b1e53 |
completed | March 8, 2026, 4:40 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0076b4819094628f1ad10b8f68 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:06 p.m.