Triple
T9558705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Basis of Make-Up |
E230613
|
entity |
| Predicate | cinematicForm |
P89781
|
FINISHED |
| Object | still images |
—
|
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: still images | Statement: [The Basis of Make-Up, cinematicForm, still images]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cinematicForm Context triple: [The Basis of Make-Up, cinematicForm, still images]
-
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.
cinematicSignificance
Indicates the degree to which something holds notable importance, influence, or impact within the realm of cinema or film history.
-
C.
filmicFunction
Indicates the role or purpose that something serves within the structure, style, or narrative function of a film.
-
D.
filmType
Indicates the specific category or genre that a film belongs to.
-
E.
filmMedium
Indicates the physical or technical format (such as film stock, digital, or video) in which a film is recorded or presented.
- F. None of above. chosen
Provenance (4 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_69ca847e53a88190a60eed7e02257f10 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd994a7e9c8190b68883c2ea45aa1a |
completed | April 1, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69ccd594d0ac8190a81bc11a3a538167 |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93e90048190a2b0d7c5c195ba98 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:03 p.m.