Triple
T32687307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 75th Golden Globe Awards |
E835759
|
entity |
| Predicate | bestFilmDramaWinner |
P8112
|
FINISHED |
| Object | Three Billboards Outside Ebbing, Missouri |
—
|
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: Three Billboards Outside Ebbing, Missouri | Statement: [75th Golden Globe Awards, bestFilmDramaWinner, Three Billboards Outside Ebbing, Missouri]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestFilmDramaWinner Context triple: [75th Golden Globe Awards, bestFilmDramaWinner, Three Billboards Outside Ebbing, Missouri]
-
A.
bestPictureWinner
chosen
Indicates that the subject is the film that won the Best Picture award in a given context or year.
-
B.
bestDirectorWinner
Indicates that the subject is the winner of a "Best Director" award for the object (such as a specific film, event, or year).
-
C.
bestScoringOfADramaticOrComedyPictureWinner
Indicates that the subject is the winner for best scoring of a dramatic or comedy motion picture.
-
D.
bestActorWinner
Indicates that the subject is the recipient of a "Best Actor" award for a particular performance or event.
-
E.
bestAssistantDirectorWinnerFilm
Indicates that a film is the work for which a particular assistant director won the Best Assistant Director 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_69f3493211388190993801216afbc2a7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c8174d8c8190a2352e6bc287abb4 |
completed | May 3, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:09 a.m.