Triple
T29228051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skyfall estate |
E740986
|
entity |
| Predicate | cinematicGenreContext |
P95473
|
FINISHED |
| Object | spy action thriller |
—
|
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: spy action thriller | Statement: [Skyfall estate, cinematicGenreContext, spy action thriller]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cinematicGenreContext Context triple: [Skyfall estate, cinematicGenreContext, spy action thriller]
-
A.
cinematicContext
Indicates the relationship in which something is situated within, shaped by, or relevant to the circumstances, style, or conventions of cinema or film.
-
B.
filmTypeContext
Indicates the contextual relationship between a film and its type or category within a specific classification or usage setting.
-
C.
cinematicForm
Indicates that something is expressed, structured, or realized through the techniques, conventions, or medium of cinema or film.
-
D.
visualGenre
chosen
Indicates the visual or stylistic category to which something belongs, such as its artistic or cinematic genre.
-
E.
cinematicSignificance
Indicates the degree to which something holds notable importance, influence, or impact within the realm of cinema or film history.
- 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_69f07cbb12bc81908c1971d9de9a8d2a |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f66437bb6481908684a8453f6c4166 |
completed | May 2, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 12:17 p.m.