Triple
T16296534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leave Her to Heaven |
E395660
|
entity |
| Predicate | AcademyAwards |
P10689
|
FINISHED |
| Object | Best Cinematography (Color) |
—
|
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 (Color) | Statement: [Leave Her to Heaven, AcademyAwards, Best Cinematography (Color)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: AcademyAwards Context triple: [Leave Her to Heaven, AcademyAwards, Best Cinematography (Color)]
-
A.
oscarAward
chosen
Indicates that an entity has received or been honored with an Academy Award (Oscar).
-
B.
AcademyAwardsYear
Indicates the specific year in which the referenced Academy Awards event took place.
-
C.
academyAwardsContext
Indicates the relationship between an entity and its context or details specifically related to the Academy Awards (e.g., nominations, wins, categories, or years).
-
D.
nationalFilmAward
Indicates that an entity has received or is associated with a National Film Award, representing official recognition in a national-level film awards system.
-
E.
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.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e2dcdac819083918f0964dd5666 |
completed | April 17, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69e219fa5508819097e9d383348bf174 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:06 a.m.