Triple
T16034751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virginia Madsen as Katherine |
E388940
|
entity |
| Predicate | filmReleaseFormat |
P55030
|
FINISHED |
| Object | theatrical release |
—
|
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: theatrical release | Statement: [Virginia Madsen as Katherine, filmReleaseFormat, theatrical release]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmReleaseFormat Context triple: [Virginia Madsen as Katherine, filmReleaseFormat, theatrical release]
-
A.
appearsInFilmFormat
Indicates that something is presented or occurs within a specific film format or medium of cinematic presentation.
-
B.
filmAdaptationFormat
Indicates the specific medium or format (e.g., feature film, TV movie, short film) in which a work has been adapted into a film.
-
C.
hasTheatricalForm
Indicates that something is associated with or presented in a particular theatrical form or style.
-
D.
filmReleaseContext
chosen
Indicates the circumstances or setting (such as time, place, or format) under which a film is released.
-
E.
filmLanguageFormat
Indicates the specific language and presentation format (e.g., dubbed, subtitled, original audio) in which a film is released or available.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1826f34c081908005bb736f1c485d |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.