Triple
T21130607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1929 Academy Awards |
E520672
|
entity |
| Predicate | mostAwardsFilmCount |
P142971
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [1929 Academy Awards, mostAwardsFilmCount, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostAwardsFilmCount Context triple: [1929 Academy Awards, mostAwardsFilmCount, 3]
-
A.
mostAwardsFilm
Indicates that a film is the one that has received the highest number of awards within a given set or context.
-
B.
mostNominationsFilm
Indicates that a film holds the highest number of nominations within a given set, context, or award event.
-
C.
mostNominationsCount
Indicates the highest number of nominations that any entity in the relevant set has received.
-
D.
academyAwardsNominationsCount
Indicates the number of times an entity has been nominated for an Academy Award.
-
E.
numberOfAcademyAwardsForBestDirector
Indicates the total count of Academy Awards received by a director for the Best Director category.
- 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_69e0b50b53048190ae34e8abbe3c5ada |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e723556ec08190a2ade96c76f9cec7 |
completed | April 21, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e5f5ed6c8c8190b31092a5d4c3de5d |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5f993240c8190847c0b08e65726c8 |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 2:56 p.m.