Triple
T1271461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Makeup and Hairstyling |
E15718
|
entity |
| Predicate | notableEarlyWinnerFilmYear |
P22883
|
FINISHED |
| Object | 1981 |
—
|
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: 1981 | Statement: [Academy Award for Best Makeup and Hairstyling, notableEarlyWinnerFilmYear, 1981]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableEarlyWinnerFilmYear Context triple: [Academy Award for Best Makeup and Hairstyling, notableEarlyWinnerFilmYear, 1981]
-
A.
notableWinningFilm
Indicates that a film has achieved notable recognition by winning a significant award or competition.
-
B.
firstAwardedForFilm
Indicates the film for which an entity (such as a person or award) was first given or received an award.
-
C.
notableEarlyWinner
chosen
Indicates that an entity is recognized for having achieved a significant win or success earlier than most others in a given context or competition.
-
D.
earlyNotableFilm
Indicates that the film is among the earlier works in which the subject gained notable recognition or significance.
-
E.
oscarBestPictureYear
Indicates the year in which a given film received the Academy Award for Best Picture.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c06ae7b88190a1e0b5232d84a7b1 |
completed | March 1, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69a4bede52a081909665d60acbe41d31 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.