Triple
T4567545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hustler |
E121945
|
entity |
| Predicate | AcademyAwardWin |
P37391
|
FINISHED |
| Object | Best Cinematography, Black-and-White |
—
|
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: Best Cinematography, Black-and-White | Statement: [The Hustler, AcademyAwardWin, Best Cinematography, Black-and-White]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: AcademyAwardWin Context triple: [The Hustler, AcademyAwardWin, Best Cinematography, Black-and-White]
-
A.
academyAwardWins
Indicates that one entity has won a specified number of Academy Awards (Oscars) or that a winning relationship exists between the entity and the Academy Award.
-
B.
oscarCategoryWon
chosen
Indicates that an entity has won an Academy Award in the specified Oscar category.
-
C.
oscarAward
Indicates that an entity has received or been honored with an Academy Award (Oscar).
-
D.
bestPictureWinner
Indicates that the subject is the film that won the Best Picture award in a given context or year.
-
E.
academyAwardForBestActress
Indicates that an entity received the Academy Award for Best Actress in a leading role.
- 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_69bd463f156881908a99aca69c5721ac |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd589faccc8190ac0354644099810d |
completed | March 20, 2026, 2:24 p.m. |
| PD | Predicate disambiguation | batch_69bd5227063c8190973155a875b013a7 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.