scores
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
scores has 6 facts recorded in Dontopedia across 4 references, with 1 live disagreement.
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (9)
Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
initializesInitializes(2)
- Evaluate
ex:evaluate - Evaluate Method
ex:evaluate-method
appendsAppends(1)
- Evaluate Method
ex:evaluate-method
appendsToAppends to(1)
- Evaluate
ex:evaluate
initializesVariableInitializes Variable(1)
- Evaluate
ex:evaluate
returnsReturns(1)
- Evaluate Method
ex:evaluate-method
storesInStores in(1)
- Store Scores
ex:store-scores
sumsSums(1)
- Average Calculation
ex:average-calculation
usesListUses List(1)
- Evaluate Method
ex:evaluate-method
Other facts (5)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | List | [1] |
| Rdf:type | List | [2] |
| Rdf:type | Python List | [3] |
| Appends | Weighted Score | [3] |
| Accumulates | accuracy-scores | [4] |
Timeline
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
References (4)
ctx:claims/beam/16dd9e83-9612-47cd-a5b2-f40bf174bdf8- full textbeam-chunktext/plain1 KB
doc:beam/16dd9e83-9612-47cd-a5b2-f40bf174bdf8Show excerpt
Would you like any additional resources or specific guidance on any part of the plan? [Turn 1130] User: I'm trying to refine my choices for retrieval tools, and I've prioritized 3 tools, expecting 75% alignment with my needs. I want to mak…
ctx:claims/beam/6798f38f-2a01-40b6-8b5e-3174089598f5- full textbeam-chunktext/plain1 KB
doc:beam/6798f38f-2a01-40b6-8b5e-3174089598f5Show excerpt
def __init__(self, criteria, weights=None): self.criteria = criteria self.weights = weights if weights else [1] * len(criteria) def evaluate(self, llm): scores = [] for criterion, weight in zip(self.…
ctx:claims/beam/d9cc5fac-3ed5-4fad-bdfb-42526df9ee93ctx:claims/beam/16a732b3-3e07-4ba8-a721-14e165b54a5e
See also
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