Triple
T25158720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 19th Academy Awards |
E626382
|
entity |
| Predicate | bestLiveActionShortTwoReelWinner |
P57772
|
FINISHED |
| Object | A Boy and His Dog |
—
|
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: A Boy and His Dog | Statement: [19th Academy Awards, bestLiveActionShortTwoReelWinner, A Boy and His Dog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestLiveActionShortTwoReelWinner Context triple: [19th Academy Awards, bestLiveActionShortTwoReelWinner, A Boy and His Dog]
-
A.
bestLiveActionShortSubjectTwoReelWinner
chosen
Indicates that the subject is the winner of the Academy Award for Best Live Action Short Film in the two-reel category.
-
B.
bestLiveActionShortOneReelWinner
Indicates that an entity has won the award for Best Live Action Short Film in the one-reel category.
-
C.
bestLiveActionShortFilmWinner
Indicates that the subject is the winner of the Best Live Action Short Film award in a given year or context.
-
D.
bestShortSubjectOneReelWinner
Indicates that the subject has won the award for best short subject in the one-reel category.
-
E.
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).
- 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_69e2ff2834ec8190b0872e2ec3d76023 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f46b8b03508190ad7ef11ca65eda05 |
completed | May 1, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 6:31 a.m.