Triple
T36922583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boy Meets Girl |
E913241
|
entity |
| Predicate | hasFilmDebutOf |
P93166
|
FINISHED |
| Object | Leos Carax as feature director |
—
|
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: Leos Carax as feature director | Statement: [Boy Meets Girl, hasFilmDebutOf, Leos Carax as feature director]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmDebutOf Context triple: [Boy Meets Girl, hasFilmDebutOf, Leos Carax as feature director]
-
A.
leadActorDebutFilmFor
Indicates that a person’s first film as a lead actor is the specified movie.
-
B.
filmDebutIn
Indicates the first film in which a person appeared or participated, marking their debut in cinema.
-
C.
theaterDebutWith
Indicates that an entity made its first appearance or performance in a theater production together with another specified entity.
-
D.
filmDebutFor
Indicates that a particular work marks the first film appearance or role of a given person.
-
E.
featureFilmDebut
chosen
Indicates that a work marks an entity’s first appearance or role in a feature-length film.
- 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_6a00372ff0e48190b3ed91f9bae9da6c |
completed | May 10, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_6a00359c1b8481909c1e43df9f5a789a |
completed | May 10, 2026, 7:37 a.m. |
Created at: May 3, 2026, 4:13 p.m.