Triple
T32560667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Eyes |
E832214
|
entity |
| Predicate | associatedFilmLeadActress |
—
|
GENERATED |
| Object | Lady Gaga |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedFilmLeadActress Context triple: [Black Eyes, associatedFilmLeadActress, Lady Gaga]
-
A.
associatedWithLeadActorOfFilm
Indicates a relationship where one entity is connected or linked in some relevant way to the lead actor of a specified film.
-
B.
leadActress
Indicates that the subject is the primary female performer in the specified film, show, or production.
-
C.
relationshipTypeWithFemaleLead
Indicates the type or nature of a relationship that an entity has with a female lead.
-
D.
hasAssociatedActress
chosen
Indicates that an entity is linked to an actress who is associated with it in a relevant context (e.g., participation, representation, or involvement).
-
E.
leadActressCharacterName
Indicates the name of the character portrayed by the lead actress in a given work.
- F. None of above.
Provenance (1 batch)
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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 1:03 a.m.