Triple
T4692956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North–South Prize |
E104076
|
entity |
| Predicate | typicalNumberOfLaureates |
P1620
|
FINISHED |
| Object | two laureates per year |
—
|
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: two laureates per year | Statement: [North–South Prize, typicalNumberOfLaureates, two laureates per year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNumberOfLaureates Context triple: [North–South Prize, typicalNumberOfLaureates, two laureates per year]
-
A.
typicalNumberOfLaureatesPerYear
chosen
Indicates the usual or average number of laureates associated with a given award or context in a single year.
-
B.
typicalNumberOfLaureatesPerCycle
Indicates the usual or average number of laureates associated with each award cycle or iteration.
-
C.
maximumNumberOfLaureatesPerYear
Indicates the highest allowable or observed count of laureates associated with a given year.
-
D.
typicalLaureateType
Indicates the usual or most common type or category of laureate associated with something.
-
E.
hasLaureate
Indicates that an entity (such as an award or prize) has a specific person or group as its laureate or recipient.
- 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_69bd43df91f481908e9add1b617b60ef |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd66059bfc8190885d26d05dd38df1 |
completed | March 20, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69bd6219da948190bbbb50f08573ab4d |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.