Triple
T33197811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 6th Academy Awards |
E849813
|
entity |
| Predicate | bestCinematographyFilm |
P37206
|
FINISHED |
| Object | A Midsummer Night’s Dream |
—
|
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: A Midsummer Night’s Dream | Statement: [6th Academy Awards, bestCinematographyFilm, A Midsummer Night’s Dream]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestCinematographyFilm Context triple: [6th Academy Awards, bestCinematographyFilm, A Midsummer Night’s Dream]
-
A.
bestCinematographyWinner
chosen
Indicates that the subject is the work or individual that won the award for best cinematography in a given context or event.
-
B.
cinematographyAwardedTo
Indicates that a cinematography-related award has been given to a particular recipient (such as a person or team) for their work.
-
C.
numberOfAcademyAwardsForBestCinematography
Indicates the number of Academy Awards received for Best Cinematography.
-
D.
bestPictureWinner
Indicates that the subject is the film that won the Best Picture award in a given context or year.
-
E.
cinematographyAwardNominee
Indicates that an entity was nominated to receive an award specifically recognizing excellence in cinematography.
- 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_69f3495efedc8190843a5728089544b9 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6e02ba6b881908dfafc52d3b75f1c |
completed | May 3, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69f6de09c2f481909f8b2545d3208c9f |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:29 a.m.