Triple
T28980140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oscars 2017 |
E734524
|
entity |
| Predicate | presenterOfBestPicture |
P180516
|
FINISHED |
| Object | Warren Beatty |
—
|
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: Warren Beatty | Statement: [Oscars 2017, presenterOfBestPicture, Warren Beatty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: presenterOfBestPicture Context triple: [Oscars 2017, presenterOfBestPicture, Warren Beatty]
-
A.
bestPictureWinner
Indicates that the subject is the film that won the Best Picture award in a given context or year.
-
B.
bestPictureNominee
Indicates that a film was officially nominated for the Best Picture award in a given awards event.
-
C.
bestDirectorWinner
Indicates that the subject is the winner of a "Best Director" award for the object (such as a specific film, event, or year).
-
D.
oscarCategoryWon
Indicates that an entity has won an Academy Award in the specified Oscar category.
-
E.
bestPictureProducer
Indicates that the subject is the producer associated with a film that won the Best Picture award.
- F. None of above. chosen
Provenance (4 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_69f05b0dd9b481908b7901e1c95ff6b2 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: April 28, 2026, 9:10 a.m.