Triple
T37106968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Supporting Actor for "Moonstruck" |
E918867
|
entity |
| Predicate | winnerFilmInCategoryAtCeremony |
P37391
|
FINISHED |
| Object | The Untouchables |
—
|
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: The Untouchables | Statement: [Academy Award for Best Supporting Actor for "Moonstruck", winnerFilmInCategoryAtCeremony, The Untouchables]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerFilmInCategoryAtCeremony Context triple: [Academy Award for Best Supporting Actor for "Moonstruck", winnerFilmInCategoryAtCeremony, The Untouchables]
-
A.
oscarCategoryWon
chosen
Indicates that an entity has won an Academy Award in the specified Oscar category.
-
B.
oscarAward
Indicates that an entity has received or been honored with an Academy Award (Oscar).
-
C.
bestPictureWinner
Indicates that the subject is the film that won the Best Picture award in a given context or year.
-
D.
cannesFilmFestivalAward
Indicates that an entity has received an award presented at the Cannes Film Festival.
-
E.
associatedAwardWinningFilm
Indicates that there is a relationship between an entity and a film with which it is connected, where that film has received an award.
- 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_69f76e9b99c8819096164b21ff5bd996 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: May 3, 2026, 4:14 p.m.