Triple
T32128352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 37th Academy Awards |
E820566
|
entity |
| Predicate | bestScreenplayBasedOnMaterialFromAnotherMedium |
P23410
|
FINISHED |
| Object | Becket |
—
|
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: Becket | Statement: [37th Academy Awards, bestScreenplayBasedOnMaterialFromAnotherMedium, Becket]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestScreenplayBasedOnMaterialFromAnotherMedium Context triple: [37th Academy Awards, bestScreenplayBasedOnMaterialFromAnotherMedium, Becket]
-
A.
bestScreenplayWriter
Indicates that the subject is recognized as the top or most outstanding writer of a screenplay, typically in comparison to other writers within a specific context or competition.
-
B.
screenplaySubject
Indicates that a screenplay is about, centers on, or takes as its main subject a particular entity or topic.
-
C.
filmAdaptationOfWork
Indicates that a film is an adaptation based on the narrative content of a specific original work.
-
D.
screenWriterAdaptationBy
chosen
Indicates that a person served as the screenwriter responsible for adapting an existing work into a screenplay.
-
E.
bookAdaptedInto
Indicates that a book has been turned into another work, typically in a different medium such as a film, TV series, or play.
- 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_69f34902d42c819083a8e6bba9a8bb9a |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b96d083881909e975a040d96c764 |
completed | May 3, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69f6b6293188819080d5041ca0adb969 |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:29 a.m.