alphas
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-08.)
alphas has 16 facts recorded in Dontopedia across 4 references, with 2 live disagreements.
Mostly:contains(3), rdf:type(2), are superiors(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (11)
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.
describesDescribes(2)
- Comment
ex:comment - Comment Entity
ex:comment_entity
attachedToAttached to(1)
- Comment
ex:comment
directedToDirected to(1)
- Poem for Alphas
ex:poem-for-alphas
expressesLoyaltyToExpresses Loyalty to(1)
- Poem for Alphas
ex:poem-for-alphas
iteratesOverIterates Over(1)
- For Loop
ex:for-loop
passesArgumentPasses Argument(1)
- Tune Alpha Call
ex:tune_alpha_call
respondsToResponds to(1)
- Wombat Fetch
ex:wombat-fetch
takesParametersTakes Parameters(1)
- Evaluate Relevance Lift
ex:evaluate-relevance-lift
Other facts (14)
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 |
|---|---|---|
| Contains | 0 | [2] |
| Contains | 1 | [2] |
| Contains | 11 | [2] |
| Rdf:type | Variable | [2] |
| Rdf:type | Parameter Collection | [4] |
| Are Superiors | Bots | [1] |
| Exists | true | [1] |
| Is Initialized by | Np.linspace | [2] |
| Described As | Range of alpha values to test | [2] |
| Created by | Np.linspace | [2] |
| Commented by | Range of alpha values to test | [2] |
| Generated by | Numpy Linspace | [3] |
| Controls | Hybrid Weighting | [3] |
| Is Iterated by | For Loop | [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:discord/blah/tpmjs-park/part-6ctx:claims/beam/8419193f-8cac-4d94-919a-b1c2084db6fd- full textbeam-chunktext/plain1 KB
doc:beam/8419193f-8cac-4d94-919a-b1c2084db6fdShow excerpt
alphas = np.linspace(0, 1, 11) # Range of alpha values to test best_alpha, best_map = {}, {} for query in queries: best_alpha[query], best_map[query] = tune_alpha(query, documents, relevant_docs[query], alphas) print(f"Best alpha f…
ctx:claims/beam/cc7e2701-5558-4a53-b31f-07382bf903bd- full textbeam-chunktext/plain1 KB
doc:beam/cc7e2701-5558-4a53-b31f-07382bf903bdShow excerpt
dense_scores = np.array([0.7, 0.3, 0.1]) # Normalize and compute hybrid scores hybrid_scores = hybrid_ranking(sparse_scores, dense_scores) print(hybrid_scores) # Optionally, sort documents based on hybrid scores sorted_indices = np.argsor…
ctx:claims/beam/e3d6146f-0be0-4107-8509-b0471fc829a9- full textbeam-chunktext/plain896 B
doc:beam/e3d6146f-0be0-4107-8509-b0471fc829a9Show excerpt
precision = precision_at_k(true_labels, predicted_labels, k=k) if precision > best_precision: best_precision = precision best_alpha = alpha print(f"Best Alpha: {best_alpha}, Best Precision@{k…
See also
Keep researching
Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.