Triple
T31649774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time Freak |
E807684
|
entity |
| Predicate | shortFilmOscarNomination |
P172605
|
FINISHED |
| Object | Academy Award for Best Live Action Short Film |
—
|
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: Academy Award for Best Live Action Short Film | Statement: [Time Freak, shortFilmOscarNomination, Academy Award for Best Live Action Short Film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shortFilmOscarNomination Context triple: [Time Freak, shortFilmOscarNomination, Academy Award for Best Live Action Short Film]
-
A.
notableShortFilm
Indicates that the subject is a short film that is recognized as notable or significant in some meaningful way.
-
B.
bestAnimatedShortFilmWinner
Indicates that one entity is the winner of the Best Animated Short Film award in relation to the other entity (such as a specific year or award event).
-
C.
bestLiveActionShortFilmWinner
Indicates that the subject is the winner of the Best Live Action Short Film award in a given year or context.
-
D.
bestLiveActionShortSubjectTwoReelWinner
Indicates that the subject is the winner of the Academy Award for Best Live Action Short Film in the two-reel category.
-
E.
filmEditingNominee
Indicates that an entity was nominated for an award recognizing excellence in film editing for a particular film or work.
- 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_69f348d9ce58819093ea2da83cbeeec1 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ac1ed23c8190ace57ffc9d8a3dc6 |
completed | May 3, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1e84b88190b025f6ca40f17a8a |
completed | May 3, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69f6aba8fba48190bc1a17117244cae1 |
completed | May 3, 2026, 1:58 a.m. |
Created at: April 30, 2026, 10:52 p.m.