Triple
T3664907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 74th Academy Awards |
E77735
|
entity |
| Predicate | mostWinsCount |
P27026
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [74th Academy Awards, mostWinsCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostWinsCount Context triple: [74th Academy Awards, mostWinsCount, 4]
-
A.
mostWinsByPlayerCount
Indicates the maximum number of wins achieved by any single player within the considered set or context.
-
B.
mostOverallWinsHolder
Indicates that the subject is the entity holding the highest total number of wins overall, compared to all other relevant entities.
-
C.
mostOverallWinsRecord
Indicates that the subject holds the record for having the greatest total number of wins compared to all others in the relevant context.
-
D.
numberOfWins
chosen
Indicates the count of times an entity has achieved victory in a relevant context or competition.
-
E.
mostConsecutiveWinsCount
Indicates the highest number of wins achieved in a row within a given sequence or context.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc400352081908c16a6a7670eb52a |
completed | March 8, 2026, 6:46 p.m. |
| PD | Predicate disambiguation | batch_69adb847e9d881909dad2ffd0f3b6c15 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:25 p.m.