Triple
T77752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nobel Prize in Physiology or Medicine |
E1554
|
entity |
| Predicate | maximumNumberOfLaureatesPerYear |
P4844
|
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: [Nobel Prize in Physiology or Medicine, maximumNumberOfLaureatesPerYear, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumNumberOfLaureatesPerYear Context triple: [Nobel Prize in Physiology or Medicine, maximumNumberOfLaureatesPerYear, 3]
-
A.
typicalNumberOfLaureatesPerYear
Indicates the usual or average number of laureates associated with a given award or context in a single year.
-
B.
hasLaureate
Indicates that an entity (such as an award or prize) has a specific person or group as its laureate or recipient.
-
C.
NobelPrizeYear
Indicates the specific year in which an entity received or was awarded a Nobel Prize.
-
D.
typicalLaureateType
Indicates the usual or most common type or category of laureate associated with something.
-
E.
lastAwarded
Indicates the most recent time or instance at which an entity received a particular award.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2559892dc81909303f2eefdc0025f |
completed | Feb. 28, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69a24eaf99e481908e8d314577e22ecf |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a25597b6c48190849c3e9e6351b983 |
completed | Feb. 28, 2026, 2:40 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.