Triple
T1664753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empire (film) |
E35984
|
entity |
| Predicate | cameraMovement |
P20442
|
FINISHED |
| Object | stationary |
—
|
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: stationary | Statement: [Empire (film), cameraMovement, stationary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cameraMovement Context triple: [Empire (film), cameraMovement, stationary]
-
A.
movementContext
Indicates the situational or environmental conditions under which a movement or motion event occurs, such as its manner, setting, or constraints.
-
B.
movementDirection
Indicates the direction or path along which an entity moves or is moving relative to a reference frame or point.
-
C.
usesMovement
Indicates that an entity performs or involves some form of movement as part of its action or behavior.
-
D.
movementIn
Indicates a relationship where an entity moves within, into, or inside a specified area, space, or container.
-
E.
cameraStyle
chosen
Indicates the characteristic visual approach or technique used by a camera in capturing or presenting imagery.
- 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_69a88606aa808190aa0b421b4271f220 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa994f92b0819084ee2f6a672334b9 |
completed | March 6, 2026, 9:07 a.m. |
| PD | Predicate disambiguation | batch_69a907d2475c8190b7ec7dccd3335eb1 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:29 p.m.