Triple
T15918832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nebraska (film) |
E386039
|
entity |
| Predicate | nationalBoardOfReviewRecognition |
P120533
|
FINISHED |
| Object | Top Ten Films of 2013 |
—
|
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: Top Ten Films of 2013 | Statement: [Nebraska (film), nationalBoardOfReviewRecognition, Top Ten Films of 2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalBoardOfReviewRecognition Context triple: [Nebraska (film), nationalBoardOfReviewRecognition, Top Ten Films of 2013]
-
A.
nationalFilmAward
Indicates that an entity has received or is associated with a National Film Award, representing official recognition in a national-level film awards system.
-
B.
nominatedIn
Indicates that an entity has been formally put forward as a candidate for an award, position, or recognition within a specific event, context, or time period.
-
C.
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.
-
D.
bestPictureNominee
Indicates that a film was officially nominated for the Best Picture award in a given awards event.
-
E.
tonyNominations
Indicates that an entity has received one or more nominations for a Tony Award.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e172b213e481909ee0c05e16229a26 |
completed | April 16, 2026, 11:37 p.m. |
Created at: April 10, 2026, 4:52 a.m.