Triple
T22150774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EMS Prize |
E547405
|
entity |
| Predicate | maximumNumberOfLaureatesPerEdition |
P147183
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [EMS Prize, maximumNumberOfLaureatesPerEdition, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumNumberOfLaureatesPerEdition Context triple: [EMS Prize, maximumNumberOfLaureatesPerEdition, 10]
-
A.
maximumNumberOfLaureatesPerYear
Indicates the highest allowable or observed count of laureates associated with a given year.
-
B.
typicalNumberOfLaureatesPerCycle
Indicates the usual or average number of laureates associated with each award cycle or iteration.
-
C.
typicalNumberOfLaureatesPerYear
Indicates the usual or average number of laureates associated with a given award or context in a single year.
-
D.
maximumAwardsToSamePerson
Indicates the maximum number of awards that can be given to the same person within the defined context or system.
-
E.
numberOfHonoreesPerPeriod
Indicates the count of honorees associated with each defined time period.
- 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_69e11e3b52088190ad5df386d01eb2fb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129f37dac8190a7cecb12f4271515 |
completed | April 28, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69e71b384e008190b723c9a0f1089d66 |
completed | April 21, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e7222d208c819098b12c13e31af629 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:33 p.m.