Triple
T31133229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Picture for Capote |
E793566
|
entity |
| Predicate | competedWithBestPictureWinner |
P46703
|
FINISHED |
| Object | Crash (2004 film) |
—
|
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: Crash (2004 film) | Statement: [Academy Award for Best Picture for Capote, competedWithBestPictureWinner, Crash (2004 film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: competedWithBestPictureWinner Context triple: [Academy Award for Best Picture for Capote, competedWithBestPictureWinner, Crash (2004 film)]
-
A.
associatedAwardWinningFilm
Indicates that there is a relationship between an entity and a film with which it is connected, where that film has received an award.
-
B.
bestPictureWinOver
chosen
Indicates that one film won the Best Picture award in preference to or instead of another film.
-
C.
bestPictureNominee
Indicates that a film was officially nominated for the Best Picture award in a given awards event.
-
D.
associatedWithAwardNominatedFilm
Indicates that an entity has a relationship to a film that has been nominated for an award.
-
E.
bestPictureWinner
Indicates that the subject is the film that won the Best Picture award in a given context or year.
- 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_69f224d1701c819094f429798290e361 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
Created at: April 29, 2026, 9:05 p.m.