Triple
T35393020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Language Lessons |
E1022991
|
entity |
| Predicate | filmingMethod |
P2760
|
FINISHED |
| Object | screenlife |
—
|
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: screenlife | Statement: [Language Lessons, filmingMethod, screenlife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmingMethod Context triple: [Language Lessons, filmingMethod, screenlife]
-
A.
filmingTechnique
chosen
Indicates the specific method or style used to capture visual content during the filming process.
-
B.
filmingState
Indicates the current production or recording status of a filming activity, such as whether it is planned, in progress, paused, or completed.
-
C.
filmSetting
Indicates the place, time, or environment in which the events of a film are set or take place.
-
D.
cinematographyIncludes
Indicates that a cinematographic work or process contains or makes use of specific visual techniques, elements, or components as part of its overall execution.
-
E.
cinematographyBy
Indicates that the cinematographic work (such as the camera work or visual style of a film or video) is created or supervised by a specified person or entity.
- 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_69f76df34ba48190bd80f0814cdcd540 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f794fd5fd08190ab39a0c8882536df |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.