Triple
T36922539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holy Motors |
E913240
|
entity |
| Predicate | EvaPortrayedBy |
P1507
|
FINISHED |
| Object | Kylie Minogue |
—
|
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: Kylie Minogue | Statement: [Holy Motors, EvaPortrayedBy, Kylie Minogue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: EvaPortrayedBy Context triple: [Holy Motors, EvaPortrayedBy, Kylie Minogue]
-
A.
filmAdaptationEvaPerformer
Indicates that the subject is a performer who played the character Eva in a film adaptation of the referenced work.
-
B.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
C.
portrayedByAlsoKnownFor
Indicates that an entity is portrayed by a person who is also notably known for another specific role or work.
-
D.
originalWestEndEvaPerformer
Indicates that the subject was the performer who originally played the role of Eva in the West End production.
-
E.
leadActressCharacterName
Indicates the name of the character portrayed by the lead actress in a given 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fdcde388819099c0d417f07b5a60 |
completed | May 5, 2026, 2:25 p.m. |
| PD | Predicate disambiguation | batch_69f7cf79ddb08190a083405cccc14137 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.