Triple
T36774805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Foreign Language Film |
E908585
|
entity |
| Predicate | winnerAt83rdAcademyAwards |
P10689
|
FINISHED |
| Object | In a Better World |
—
|
NE NERFINISHED |
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: In a Better World | Statement: [Academy Award for Best Foreign Language Film, winnerAt83rdAcademyAwards, In a Better World]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerAt83rdAcademyAwards Context triple: [Academy Award for Best Foreign Language Film, winnerAt83rdAcademyAwards, In a Better World]
-
A.
oscarCategoryWon
Indicates that an entity has won an Academy Award in the specified Oscar category.
-
B.
bestPictureWinner
Indicates that the subject is the film that won the Best Picture award in a given context or year.
-
C.
bestScoringOfADramaticOrComedyPictureWinner
Indicates that the subject is the winner for best scoring of a dramatic or comedy motion picture.
-
D.
oscarAward
chosen
Indicates that an entity has received or been honored with an Academy Award (Oscar).
-
E.
bestActorWinner
Indicates that the subject is the recipient of a "Best Actor" award for a particular performance or event.
- 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_69f76e798aa08190ace31098d1b13e9f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:12 p.m.