Triple
T5294080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Man Who Wasn't There |
E119811
|
entity |
| Predicate | filmingInColor |
P13343
|
FINISHED |
| Object | black-and-white |
—
|
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: black-and-white | Statement: [The Man Who Wasn't There, filmingInColor, black-and-white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmingInColor Context triple: [The Man Who Wasn't There, filmingInColor, black-and-white]
-
A.
hasFilmColorType
chosen
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
-
B.
filmedFor
Indicates that something was recorded or produced specifically for a particular purpose, audience, platform, or project.
-
C.
filmingDate
Indicates the date on which the filming or recording of a work took place.
-
D.
filmingState
Indicates the current production or recording status of a filming activity, such as whether it is planned, in progress, paused, or completed.
-
E.
cinematographyBy
Indicates that the cinematographic work (such as the camera work or visual style of a film or video) is created or supervised by a specified person or entity.
- 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_69bd446f22b88190b6a47fb91c68a3e7 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8682d18c8190bbb35cc75c8a7c12 |
completed | March 20, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69bd844dfdac819086efedd1cbebff84 |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:52 p.m.