Dontopedia

max_synonyms_per_token

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)

max_synonyms_per_token has 4 facts recorded in Dontopedia across 2 references, with 1 live disagreement.

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

Inbound mentions (5)

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.

usesParameterUses Parameter(2)

isSlicedByIs Sliced by(1)

limitedByLimited by(1)

limitsToLimits to(1)

Other facts (3)

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.

3 facts
PredicateValueRef
Rdf:typeParameter[1]
Rdf:typeConfiguration Parameter[2]
ConstrainsToken Synonyms[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.

typebeam/80a16c0b-7043-48ab-aeb5-68a3a00737cb
ex:Parameter
labelbeam/80a16c0b-7043-48ab-aeb5-68a3a00737cb
max_synonyms_per_token
typebeam/b27efc86-7008-4384-852a-049d06d255cb
ex:ConfigurationParameter
constrainsbeam/b27efc86-7008-4384-852a-049d06d255cb
ex:token-synonyms

References (2)

2 references
  1. ctx:claims/beam/80a16c0b-7043-48ab-aeb5-68a3a00737cb
    • full textbeam-chunk
      text/plain1012 Bdoc:beam/80a16c0b-7043-48ab-aeb5-68a3a00737cb
      Show excerpt
      expanded_query = ' '.join(expanded_query_parts) end_time = time.time() latency = end_time - start_time print(f"Expanded Query: {expanded_query}, Latency: {latency:.4f} seconds") return expanded_query # Test th
  2. ctx:claims/beam/b27efc86-7008-4384-852a-049d06d255cb
    • full textbeam-chunk
      text/plain1 KBdoc:beam/b27efc86-7008-4384-852a-049d06d255cb
      Show excerpt
      entities = [(ent.text, ent.label_) for ent in doc.ents] # Extract synonyms for each token synonyms = [] for token in tokens: pos = get_wordnet_pos(nltk.pos_tag([token])[0][1]) synsets = wordnet.synsets(t

See also

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