Dontopedia

Corrected Query String

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)

Corrected Query String has 4 facts recorded in Dontopedia across 4 references, with 1 live disagreement.

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

Inbound mentions (7)

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.

returnsReturns(3)

displaysDisplays(1)

firstElementFirst Element(1)

hasReturnValueHas Return Value(1)

tupleElementsTuple Elements(1)

Other facts (4)

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.

4 facts
PredicateValueRef
Rdf:typeString[1]
Rdf:typeString[2]
Rdf:typeString[3]
Rdf:typeString[4]

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/28ff3364-2017-4558-946d-63674a03e0f4
ex:String
typebeam/85127f85-a5ab-4ae2-8c3e-9fe01295672a
ex:String
typebeam/ba8f0f6e-4076-45ec-b8ac-81b951e5391d
ex:String
typebeam/9ab8fe53-eb32-42d9-8eac-c30e73177819
ex:String

References (4)

4 references
  1. ctx:claims/beam/28ff3364-2017-4558-946d-63674a03e0f4
    • full textbeam-chunk
      text/plain1 KBdoc:beam/28ff3364-2017-4558-946d-63674a03e0f4
      Show excerpt
      self.context_window = 5 # considering 5 words before and after the target word self.common_misspellings = { 'loking': 'looking', 'improove': 'improve', 'spelng': 'spelling' }
  2. ctx:claims/beam/85127f85-a5ab-4ae2-8c3e-9fe01295672a
    • full textbeam-chunk
      text/plain1 KBdoc:beam/85127f85-a5ab-4ae2-8c3e-9fe01295672a
      Show excerpt
      ### Optimized Implementation Here's an optimized version of your code: ```python import hunspell from concurrent.futures import ThreadPoolExecutor, as_completed import time # Load the Hunspell dictionary once hspell = hunspell.HunSpell(
  3. ctx:claims/beam/ba8f0f6e-4076-45ec-b8ac-81b951e5391d
    • full textbeam-chunk
      text/plain1 KBdoc:beam/ba8f0f6e-4076-45ec-b8ac-81b951e5391d
      Show excerpt
      nltk.download('words') word_list = set(words.words()) # Define a function to correct a query using NLTK def correct_query_nltk(query): # Split the query into words words = query.split() # Correct each word corrected_wo
  4. ctx:claims/beam/9ab8fe53-eb32-42d9-8eac-c30e73177819

See also

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