Triple
T16004551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kris Wu |
E388180
|
entity |
| Predicate | hasFilmographyType |
P120732
|
FINISHED |
| Object | feature films |
—
|
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: feature films | Statement: [Kris Wu, hasFilmographyType, feature films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmographyType Context triple: [Kris Wu, hasFilmographyType, feature films]
-
A.
hasWorkedOnFilmBy
Indicates that one entity has worked on a film that was created, directed, or otherwise authored by another entity.
-
B.
hasFilmCareer
Indicates that an entity has been professionally involved in the film industry as a career.
-
C.
genreOfWorkActedIn
Indicates that an entity is the genre category of a work in which another entity performed or acted.
-
D.
partOfFilmographyOf
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.
-
E.
actsIn
Indicates that an entity performs or appears in a creative work, such as a film, play, or show.
- F. None of above. chosen
Provenance (4 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142dc081c819082527e3fa8773460 |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e173af801c8190bfc0f602831bb594 |
completed | April 16, 2026, 11:41 p.m. |
Created at: April 10, 2026, 4:55 a.m.