Triple
T32647313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 73rd Golden Globe Awards |
E834628
|
entity |
| Predicate | bestSupportingActorSeriesMiniseriesOrTelevisionFilm |
P177602
|
FINISHED |
| Object | Christian Slater |
—
|
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: Christian Slater | Statement: [73rd Golden Globe Awards, bestSupportingActorSeriesMiniseriesOrTelevisionFilm, Christian Slater]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestSupportingActorSeriesMiniseriesOrTelevisionFilm Context triple: [73rd Golden Globe Awards, bestSupportingActorSeriesMiniseriesOrTelevisionFilm, Christian Slater]
-
A.
bestSupportingActorWinner
Indicates that an entity has received the award for Best Supporting Actor for a particular work or event.
-
B.
bestSupportingActorWinningFilm
Indicates that a film is the one for which an actor won the Best Supporting Actor award.
-
C.
bestSupportingActorFilm
Indicates the film for which a person received the Best Supporting Actor award.
-
D.
bestSupportingActressWinner
Indicates that the subject is the person who won the Best Supporting Actress award for the specified work, year, or event.
-
E.
bestSupportingActressFilm
Indicates the film for which a person received or was nominated for a Best Supporting Actress 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_69f3492e773c81908afc10651e46cad3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7009d39508190af7301f824615e88 |
completed | May 3, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
| PDg | Predicate description generation | batch_69f6ffb7554881908993d6d2ffbcf8f5 |
completed | May 3, 2026, 7:56 a.m. |
Created at: May 1, 2026, 1:07 a.m.