Triple
T34479795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephanie Zinone |
E885149
|
entity |
| Predicate | filmDebutOfActor |
P124816
|
FINISHED |
| Object | Michelle Pfeiffer in a leading role |
—
|
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: Michelle Pfeiffer in a leading role | Statement: [Stephanie Zinone, filmDebutOfActor, Michelle Pfeiffer in a leading role]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmDebutOfActor Context triple: [Stephanie Zinone, filmDebutOfActor, Michelle Pfeiffer in a leading role]
-
A.
filmDebutFor
Indicates that a particular work marks the first film appearance or role of a given person.
-
B.
filmDebutIn
Indicates the first film in which a person appeared or participated, marking their debut in cinema.
-
C.
yearOfFilmDebutForActor
Indicates the calendar year in which an actor first appeared in a film.
-
D.
leadActorDebutFilmFor
Indicates that a person’s first film as a lead actor is the specified movie.
-
E.
filmDebutActorForCharacter
chosen
Indicates that an actor is making their first film appearance in the role of a specific 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_69f349c947fc81909d30b53c194d6ea1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2:01 a.m.