Triple
T5253210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australian Film Institute |
E118636
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object | Australia |
E876
|
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: Australia | Statement: [Australian Film Institute, operatesIn, Australia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Australia Context triple: [Australian Film Institute, operatesIn, Australia]
-
A.
Australia
chosen
Australia is a large island continent and sovereign country in the Southern Hemisphere, known for its unique wildlife, diverse landscapes, and major cities such as Sydney and Melbourne.
-
B.
Aust
Aust is a small village in South Gloucestershire, England, situated near the Severn Estuary and known historically for its ferry crossing and proximity to the Severn Bridge.
-
C.
Tasmania
Tasmania is an island state of Australia known for its rugged wilderness, unique wildlife, and relatively cool maritime climate.
-
D.
AU
AU is the commonly used abbreviation for the African Union, a continental organization that promotes political and economic cooperation among African states.
-
E.
AU
AU is the commonly used abbreviation for Anna University, a prominent public technical university based in Chennai, India.
- 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_69bd446978108190bb5f9c5c23d93f88 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b7cd7f4819098e591df07564a52 |
completed | March 20, 2026, 4:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe72c91c8190ab0f988dca420399 |
completed | March 21, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:50 p.m.