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Similarity List Computation

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)

Similarity List Computation has 3 facts recorded in Dontopedia across 2 references, with 1 live disagreement.

3 facts·2 predicates·2 sources·1 in dispute
Maturity scale raw canonical shape-checked rule-derived certified

Rdf:typein disputerdf:type

Producesproduces

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.

3 undated
—
producesbeam/5e1fccc0-109f-4d58-b6c4-6482a168aad7
ex:similarities
—
typebeam/5d8a681b-1fe3-4aff-8534-8603ba9d9bfc
ex:List-Comprehension
—
typebeam/5e1fccc0-109f-4d58-b6c4-6482a168aad7
ex:ListComprehension

References (2)

2 references
  1. [1]beam-chunk2 facts
    customctx:claims/beam/5e1fccc0-109f-4d58-b6c4-6482a168aad7
    • full textbeam-chunk
      text/plain1 KBdoc:beam/5e1fccc0-109f-4d58-b6c4-6482a168aad7
      Show excerpt
      for word, synonyms in thesaurus.items(): word_embedding = get_contextual_embeddings(word) similarities = [np.dot(term_embedding, get_contextual_embeddings(syn)) for syn in synonyms] closest_synonyms.extend([synon…
  2. [2]beam-chunk1 fact
    customctx:claims/beam/5d8a681b-1fe3-4aff-8534-8603ba9d9bfc
    • full textbeam-chunk
      text/plain1 KBdoc:beam/5d8a681b-1fe3-4aff-8534-8603ba9d9bfc
      Show excerpt
      inputs = tokenizer(term, return_tensors='pt', padding=True, truncation=True) outputs = model(**inputs) embeddings = outputs.last_hidden_state.mean(dim=1) # Mean pooling return embeddings ``` ### Step 4: Retrieve Synonyms B…

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