Triple
T24596958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Supporting Actor for Viva Zapata! |
E608702
|
entity |
| Predicate | winnerOccupation |
P107055
|
FINISHED |
| Object | actor |
—
|
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: actor | Statement: [Academy Award for Best Supporting Actor for Viva Zapata!, winnerOccupation, actor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerOccupation Context triple: [Academy Award for Best Supporting Actor for Viva Zapata!, winnerOccupation, actor]
-
A.
winnerProfession
chosen
Indicates that the associated profession is the occupation or field of work of the winner in a given event or competition.
-
B.
representedOccupation
Indicates that one entity has served as an official or formal representative of another entity’s occupation or professional role.
-
C.
significantOccupation
Indicates that an occupation plays a major or defining role in an entity’s life, status, or identity.
-
D.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
-
E.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
- 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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.