Triple
T24036653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 52nd Annual Grammy Awards |
E595250
|
entity |
| Predicate | mostAwardsWinnerCount |
P154615
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [52nd Annual Grammy Awards, mostAwardsWinnerCount, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostAwardsWinnerCount Context triple: [52nd Annual Grammy Awards, mostAwardsWinnerCount, 6]
-
A.
mostNominationsCount
Indicates the highest number of nominations that any entity in the relevant set has received.
-
B.
mostAwardsLeaderTotal
Indicates that the subject holds the highest total number of awards compared to all others in the relevant group or context.
-
C.
numberOfAwards
Indicates the total count of awards that have been received by an entity.
-
D.
mostAwardsFilmCount
Indicates the total number of awards received by the film that holds the record for having the most awards.
-
E.
mostAwardsArtistCount
Indicates the number of artists who share the highest total count of awards within a given context.
- 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_69e288bf45f08190a1b6ed8cd0b9e86b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d8d5fdc48190a037cf9447309356 |
completed | April 29, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 9:56 p.m.