Triple
T8625484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mother (1926 film) |
E204269
|
entity |
| Predicate | filmStyle |
P41012
|
FINISHED |
| Object | realism combined with montage |
—
|
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: realism combined with montage | Statement: [Mother (1926 film), filmStyle, realism combined with montage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmStyle Context triple: [Mother (1926 film), filmStyle, realism combined with montage]
-
A.
filmType
Indicates the specific category or genre that a film belongs to.
-
B.
hasFilmStyle
chosen
Indicates that a film exhibits or is characterized by a particular cinematic style or aesthetic approach.
-
C.
filmTypeContext
Indicates the contextual relationship between a film and its type or category within a specific classification or usage setting.
-
D.
filmSetting
Indicates the place, time, or environment in which the events of a film are set or take place.
-
E.
filmicFunction
Indicates the role or purpose that something serves within the structure, style, or narrative function of a film.
- 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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:26 p.m.