Triple
T977371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australian Film Institute Award for Best Direction |
E21086
|
entity |
| Predicate | presentedBy |
P83
|
FINISHED |
| Object | AFI |
E56484
|
NE 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: AFI | Statement: [Australian Film Institute Award for Best Direction, presentedBy, AFI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AFI Context triple: [Australian Film Institute Award for Best Direction, presentedBy, AFI]
-
A.
American Film Institute
chosen
The American Film Institute is a U.S.-based nonprofit organization dedicated to preserving the legacy of motion pictures and honoring excellence in the art of filmmaking.
-
B.
AMA
AMA is the leading professional association and lobbying group representing physicians and medical students in the United States.
-
C.
AFN
AFN is an abbreviation commonly used to refer to French North Africa, the former French colonial territories in the Maghreb region of North Africa.
-
D.
AF
AF is the two-letter ISO 3166-1 alpha-2 country code assigned to Afghanistan for international standardization and referencing.
-
E.
AF
AF is the two-letter IATA airline designator assigned to Air France, the flag carrier of France.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b46344048190b7a13b8f3ad9f455 |
completed | March 1, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac170e8a008190a40001224f8dae2a |
completed | March 7, 2026, 12:16 p.m. |
Created at: March 1, 2026, 7:40 p.m.