Triple
T379779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gone with the Wind |
E8652
|
entity |
| Predicate | oscarBestPicture |
P8112
|
FINISHED |
| Object | Academy Awards 1940 |
—
|
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: Academy Awards 1940 | Statement: [Gone with the Wind, oscarBestPicture, Academy Awards 1940]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oscarBestPicture Context triple: [Gone with the Wind, oscarBestPicture, Academy Awards 1940]
-
A.
oscarBestPictureYear
Indicates the year in which a given film received the Academy Award for Best Picture.
-
B.
bestPictureWinner
chosen
Indicates that the subject is the film that won the Best Picture award in a given context or year.
-
C.
oscarRecord
Indicates that an entity has a record or entry associated with the Oscars, such as a nomination, win, or related recognition.
-
D.
bestActorWinner
Indicates that the subject is the recipient of a "Best Actor" award for a particular performance or event.
-
E.
mostAwardsFilm
Indicates that a film is the one that has received the highest number of awards within a given set or context.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec2b07248190979229bad3a741c9 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e964d4b481909290e474b0341e3c |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.