Triple
T34297061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Actor for Being There |
E880058
|
entity |
| Predicate | coStarsInFilm |
P129510
|
FINISHED |
| Object | Shirley MacLaine |
—
|
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: Shirley MacLaine | Statement: [Academy Award for Best Actor for Being There, coStarsInFilm, Shirley MacLaine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coStarsInFilm Context triple: [Academy Award for Best Actor for Being There, coStarsInFilm, Shirley MacLaine]
-
A.
coStarOfFilm
Indicates that two or more performers appeared together as cast members in the same film.
-
B.
directorAlsoStarred
Indicates that the person who directed a work also acted or performed as a star in that same work.
-
C.
actúaEn
Indicates that an actor or performer takes part in or appears in a specific production, such as a film, play, or television show.
-
D.
filmCoStar
chosen
Indicates that two people appeared together as co-actors in the same film.
-
E.
filmAssociatedWith
Indicates a general relationship or connection between a film and another entity, such as a person, organization, event, or 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_69f349b79f6c81909cb468c92c39c74d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71c35327c8190884f1bfe12bd2cd7 |
completed | May 3, 2026, 9:58 a.m. |
| PD | Predicate disambiguation | batch_69f71822d0e88190ac9731c7ae5a4def |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 1:57 a.m.