Triple
T26392065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ika |
E663437
|
entity |
| Predicate | workFilmLanguageApproach |
P65544
|
FINISHED |
| Object | minimal intelligible dialogue |
—
|
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: minimal intelligible dialogue | Statement: [Ika, workFilmLanguageApproach, minimal intelligible dialogue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workFilmLanguageApproach Context triple: [Ika, workFilmLanguageApproach, minimal intelligible dialogue]
-
A.
actingApproach
Indicates the manner, method, or style in which an entity performs an action or carries out a behavior.
-
B.
filmLanguageFormat
Indicates the specific language and presentation format (e.g., dubbed, subtitled, original audio) in which a film is released or available.
-
C.
filmicFunction
chosen
Indicates the role or purpose that something serves within the structure, style, or narrative function of a film.
-
D.
directorialStyle
Indicates the characteristic manner or approach a director consistently uses in creating and shaping their works.
-
E.
workFilmType
Indicates the type or category of film associated with a particular work.
- 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_69ee883823988190b418b111be28a44a |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f610c024f081908237794984538566 |
completed | May 2, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f60b89cc048190a9feb24466006be0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 26, 2026, 11:26 p.m.