Triple
T20816604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bolero (1984 film) |
E512454
|
entity |
| Predicate | leadActorSpouseOfDirector |
P110080
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Bolero (1984 film), leadActorSpouseOfDirector, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorSpouseOfDirector Context triple: [Bolero (1984 film), leadActorSpouseOfDirector, yes]
-
A.
hasSpouseActorsInLeads
chosen
Indicates that the primary leading roles in a work are performed by actors who are spouses of each other.
-
B.
directorSpouseInCast
Indicates that a film’s director is married to someone who appears as a cast member in that same film.
-
C.
spouseAppearsIn
Indicates that the spouse of a given person appears or is featured in a specified work, context, or setting.
-
D.
hasSpouseInTVSeries
Indicates that one person is the spouse of another person within the context of a specific TV series.
-
E.
spouseCharacterOf
Indicates a marital relationship where one character is the spouse of another character.
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2f3473c81908c43a2ec242b1acd |
completed | April 21, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69e5c99ca55481908e8d434fa901cfd6 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:41 p.m.