Triple
T11318886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "You’re out of order! You’re out of order! The whole trial is out of order!" |
E268038
|
entity |
| Predicate | partOfSceneType |
P48736
|
FINISHED |
| Object | trial scene |
—
|
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: trial scene | Statement: ["You’re out of order! You’re out of order! The whole trial is out of order!", partOfSceneType, trial scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfSceneType Context triple: ["You’re out of order! You’re out of order! The whole trial is out of order!", partOfSceneType, trial scene]
-
A.
partOfScene
chosen
Indicates that one entity functions as a component or element within a larger scene or setting involving another entity.
-
B.
performedInSceneType
Indicates that an action or event was carried out within a scene of a specified type or category.
-
C.
filmSceneType
Indicates the type or category of a scene within a film, such as its narrative function, style, or setting.
-
D.
sceneFeature
Indicates a characteristic, element, or attribute that is present within or helps define a particular scene.
-
E.
sceneLabel
Indicates the categorical label or type assigned to an entire scene based on its overall content or context.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9de875481908acfa56015d4b46f |
completed | April 9, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69d787ad575081908274280bf75d95fd |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.