Triple
T8956792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red River |
E213489
|
entity |
| Predicate | filmVersion |
P67600
|
FINISHED |
| Object | theatrical cut |
—
|
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 cut | Statement: [Red River, filmVersion, theatrical cut]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmVersion Context triple: [Red River, filmVersion, theatrical cut]
-
A.
versionUsedInFilm
chosen
Indicates that a particular version or edition of a work is the one that was used in a specific film.
-
B.
filmCharacterVersionOf
Indicates that one character is a specific film adaptation or portrayal of another character originating from a different version or medium.
-
C.
hasFilmVersionStatus
Indicates whether and how a work has been adapted into a film, specifying the status of that film version.
-
D.
movieVariantName
Indicates that one movie is known by an alternative or variant name (such as a translated, regional, or re-release title).
-
E.
filmMovement
Indicates the cinematic movement or stylistic school with which a film is associated.
- 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_69ca8399ad2081909f8fa41d4314c215 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6728965881908e9f14aaee0c5a18 |
completed | April 1, 2026, 12:30 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed74d288190b712d739805579dc |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7 p.m.