Triple
T13345219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 14th Academy Awards |
E317930
|
entity |
| Predicate | bestActorWinner |
P8115
|
FINISHED |
| Object | Gary Cooper |
E62558
|
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: Gary Cooper | Statement: [14th Academy Awards, bestActorWinner, Gary Cooper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gary Cooper Context triple: [14th Academy Awards, bestActorWinner, Gary Cooper]
-
A.
Gary Cooper
chosen
Gary Cooper was an iconic American film actor renowned for his understated, stoic performances in classic Hollywood films, including major roles in Westerns and dramas.
-
B.
Clark Gable
Clark Gable was a legendary American film actor, best known for his charismatic leading roles in classic Hollywood films such as "Gone with the Wind."
-
C.
John Clark Gable
John Clark Gable is an American former racing driver and the only son of legendary Hollywood actor Clark Gable.
-
D.
Glenn Ford
Glenn Ford was a Canadian-American film actor renowned for his versatile performances in classic Hollywood movies such as "Gilda," "The Big Heat," and "Blackboard Jungle."
-
E.
Melvyn Douglas
Melvyn Douglas was an acclaimed American actor known for his sophisticated screen presence and award-winning performances in both classic Hollywood films and later character roles.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e89c65c819093f3bea11d6073c5 |
completed | April 11, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda9009ce88190b77c8f02f38107e1 |
completed | May 8, 2026, 9:12 a.m. |
Created at: April 9, 2026, 9:31 p.m.