Triple
T37328942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip Leverhulme Prize |
E926685
|
entity |
| Predicate | numberOfPrizesPerYear |
P92284
|
FINISHED |
| Object | up to 30 |
—
|
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: up to 30 | Statement: [Philip Leverhulme Prize, numberOfPrizesPerYear, up to 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPrizesPerYear Context triple: [Philip Leverhulme Prize, numberOfPrizesPerYear, up to 30]
-
A.
prizesAreAnnual
Indicates that the prizes are awarded or given out once every year.
-
B.
numberOfAwardsPerYear
chosen
Indicates the number of awards associated with an entity within a given year.
-
C.
maximumNumberOfLaureatesPerYear
Indicates the highest allowable or observed count of laureates associated with a given year.
-
D.
maximumNumberOfLaureatesPerEdition
Indicates the highest number of laureates that can be awarded in a single edition of a given prize or event.
-
E.
numberOfWinnersPerSeason
Indicates the relationship that specifies how many winners are associated with each individual season.
- 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_69f76eb386d88190a8d511aa11540dfc |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.