Triple
T26729738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Actress for Requiem for a Dream |
E673934
|
entity |
| Predicate | didSheWin |
P161176
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Academy Award for Best Actress for Requiem for a Dream, didSheWin, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: didSheWin Context triple: [Academy Award for Best Actress for Requiem for a Dream, didSheWin, no]
-
A.
wonBy
Indicates that a contest, game, or competition is decided in favor of a particular participant or side.
-
B.
winnerState
Indicates the state or condition of an entity that has achieved victory or been declared the winner in a given context.
-
C.
gameWinner
Indicates which participant or team has won a particular game or match.
-
D.
wonAt
Indicates that one entity achieved victory or success in a specific event, competition, or context.
-
E.
winnerDam
Indicates that the subject entity is the dam (mother) of an offspring that has won a specified race or competition.
- F. None of above. chosen
Provenance (4 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_69eecda57ab481909424e98f2835e7d8 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f61840ecac81908b7168d153f2000d |
completed | May 2, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69f60b8dfa0c8190864e1a940024d0a0 |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f6106d346c8190868489f36c65b6ec |
completed | May 2, 2026, 2:55 p.m. |
Created at: April 27, 2026, 3:44 a.m.