Triple
T16648271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cary Grant as Roger Thornhill |
E404531
|
entity |
| Predicate | partOfActorFilmography |
P15620
|
FINISHED |
| Object | Cary Grant filmography |
—
|
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: Cary Grant filmography | Statement: [Cary Grant as Roger Thornhill, partOfActorFilmography, Cary Grant filmography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfActorFilmography Context triple: [Cary Grant as Roger Thornhill, partOfActorFilmography, Cary Grant filmography]
-
A.
partOfFilmographyOf
chosen
Indicates that a work (such as a film, show, or role) is included in the body of screen-related works credited to a particular person.
-
B.
actsIn
Indicates that an entity performs or appears in a creative work, such as a film, play, or show.
-
C.
filmAssociatedWith
Indicates a general relationship or connection between a film and another entity, such as a person, organization, event, or work.
-
D.
has part in role
Indicates that an entity participates as a component or constituent specifically in a defined role within a larger whole or process.
-
E.
hasFilmographyType
Indicates the type or category of film-related work associated with an entity (e.g., actor, director, producer) within its filmography.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad794388190b2817d2ec5ff0de0 |
completed | April 18, 2026, 12:36 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.