Basic Thesaurus Lookup Loop
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
Basic Thesaurus Lookup Loop has 8 facts recorded in Dontopedia across 2 references, with 2 live disagreements.
Mostly:contains(3), precedes(2), rdf:type(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (2)
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.
followsFollows(1)
- Profiling Code Block
ex:profiling-code-block
hasImplementationHas Implementation(1)
- Thesaurus Lookup Function
ex:thesaurus-lookup-function
Other facts (7)
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 | Initial for Loop | [2] |
| Contains | Initial Lookup Call | [2] |
| Contains | Initial Print Call | [2] |
| Precedes | Evaluation Code Block | [1] |
| Precedes | Profiling Code Block | [2] |
| Rdf:type | Code Block | [2] |
| Implements | Thesaurus Lookup Function | [2] |
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 (2)
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/7bbf6936-789a-4b51-9607-a3b858a8c50f- full textbeam-chunktext/plain1 KB
doc:beam/7bbf6936-789a-4b51-9607-a3b858a8c50fShow excerpt
for word in words: synonyms = thesaurus_lookup(word) print(synonyms) pr.disable() s = io.StringIO() sortby = 'cumulative' ps = pstats.Stats(pr, stream=s).sort_stats(sortby) ps.print_stats() print(s.getvalue()) ``` ### Sampling Im…
See also
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