Triple
T37129727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leslie Mann as Patty Peterson |
E919483
|
entity |
| Predicate | cinematographyByInFilm |
P1953
|
FINISHED |
| Object | Sharon Calahan |
—
|
NE NERFINISHED |
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: Sharon Calahan | Statement: [Leslie Mann as Patty Peterson, cinematographyByInFilm, Sharon Calahan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cinematographyByInFilm Context triple: [Leslie Mann as Patty Peterson, cinematographyByInFilm, Sharon Calahan]
-
A.
cinematographyBy
chosen
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.
-
B.
cinematographyIncludes
Indicates that a cinematographic work or process contains or makes use of specific visual techniques, elements, or components as part of its overall execution.
-
C.
cinematographyType
Indicates the specific style or method of cinematography used in creating a film or visual work.
-
D.
cinematographySource
Indicates the origin or provider from which the cinematography of a work was obtained or derived.
-
E.
cinematographyAwardedTo
Indicates that a cinematography-related award has been given to a particular recipient (such as a person or team) for their 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_69f76e9d13e48190a108f7fbf80ff375 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb344c60f8819090f2e21e1e61d621 |
completed | May 6, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69fb2f642db08190b562725502c74ea6 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:15 p.m.