Triple
T6247175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australian Film Institute Award for Best Original Screenplay |
E139747
|
entity |
| Predicate | workTypeRecognized |
P1366
|
FINISHED |
| Object | screenplay |
—
|
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: screenplay | Statement: [Australian Film Institute Award for Best Original Screenplay, workTypeRecognized, screenplay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workTypeRecognized Context triple: [Australian Film Institute Award for Best Original Screenplay, workTypeRecognized, screenplay]
-
A.
hasWorkRecognizedBy
Indicates that one entity’s work, creation, or contribution has been formally acknowledged, honored, or cited by another entity.
-
B.
typeOfWork
chosen
Indicates the kind or category of work associated with or performed by an entity.
-
C.
originallyFromWorkType
Indicates that one entity was derived, adapted, or sourced from an original work of a specified type (e.g., book, film, artwork).
-
D.
worksTo
Indicates that one entity performs work or exerts effort in order to achieve, support, or contribute to another entity or outcome.
-
E.
workCharacterType
Indicates that a work involves or features a character of a specified type or 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0631f511c81908d413320efdce42e |
completed | March 22, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c056037bf88190a0a3fe7429345d0b |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:23 p.m.