used-forrdfs:labelOther 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.
rdf:typeRdf:type(1)ex:word-embeddingsTimeline 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/af03eb85-c312-424a-9087-37fc4052b114- **Entity Linking**: Entity linking techniques can map OOV terms to known entities, providing more accurate replacements. - **Specialized Resources**: Many domains have their own specialized knowledge graphs that can be leveraged for more …
doc:beam/34094d4f-c249-4e79-922e-dfb9f6ea172aword_embeddings = KeyedVectors.load_word2vec_format('path/to/word2vec.txt', binary=False) def find_nearest_neighbor(embedding, word_embeddings): min_distance = float('inf') nearest_neighbor = None for word in word_embeddings.in…
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