Similarity Measurement
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
Similarity Measurement has 5 facts recorded in Dontopedia across 2 references, with 2 live disagreements.
5 facts·3 predicates·2 sources·2 in dispute
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
Similarity Measurement has 5 facts recorded in Dontopedia across 2 references, with 2 live disagreements.
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.
usedForUsed for(1)ex:faiss-index-flat-l2Timeline 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.
doc:beam/5e1fccc0-109f-4d58-b6c4-6482a168aad7for 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…
doc:beam/b500ea7f-bdd6-4e4f-85ea-3886a6ea5a21- We create a `faiss.IndexFlatL2` index, which uses the L2 distance metric to measure similarity. 3. **Add Embeddings to the Index**: - We add the document embeddings to the index using the `add` method. 4. **Generate a Random Query…
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