Triple
T15066283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 73rd Academy Awards |
E379764
|
entity |
| Predicate | bestActorWinner |
P8115
|
FINISHED |
| Object | Russell Crowe |
E4560
|
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: Russell Crowe | Statement: [73rd Academy Awards, bestActorWinner, Russell Crowe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Russell Crowe Context triple: [73rd Academy Awards, bestActorWinner, Russell Crowe]
-
A.
Russell Crowe
chosen
Russell Crowe is an Academy Award–winning New Zealand–born actor renowned for intense, transformative performances in films such as Gladiator and A Beautiful Mind.
-
B.
Anthony LaPaglia
Anthony LaPaglia is an Australian actor best known for his Emmy-winning role on the television series "Without a Trace" and acclaimed performances in films such as "Lantana" and "Balibo."
-
C.
Guy Pearce
Guy Pearce is an Australian actor known for his versatile performances in films such as "Memento," "L.A. Confidential," and "The King's Speech."
-
D.
Eric Bana
Eric Bana is an Australian actor known for his versatile performances in films such as "Hulk," "Munich," and "Troy."
-
E.
Ben Mendelsohn
Ben Mendelsohn is an Australian actor known for his intense character roles in film and television, including prominent villains in major Hollywood productions.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedeea750c819082d8823c9ab6c5a2 |
completed | April 15, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5cb04e88190a42bb0e516df61bc |
completed | May 9, 2026, 3:11 a.m. |
Created at: April 10, 2026, 3:02 a.m.