Dontopedia

Train Encodings

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Train Encodings has 4 facts recorded in Dontopedia across 2 references.

4 facts·4 predicates·2 sources

Mostly:part of(1), rdf:type(1), is assigned by(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (2)

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hasPartHas Part(1)

initializedWithInitialized With(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
Part ofTrain Dataset[1]
Rdf:typeVariable[2]
Is Assigned byTokenizer Call[2]
Assigned byTokenizer Call[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.

partOfbeam/20f0272f-7b57-4162-9e25-c21ae614367b
ex:train-dataset
typebeam/e8aa5db9-3e5f-4e4b-b042-f2179d9b2b8f
ex:Variable
isAssignedBybeam/e8aa5db9-3e5f-4e4b-b042-f2179d9b2b8f
ex:tokenizer-call
assignedBybeam/e8aa5db9-3e5f-4e4b-b042-f2179d9b2b8f
ex:tokenizer-call

References (2)

2 references
  1. ctx:claims/beam/20f0272f-7b57-4162-9e25-c21ae614367b
    • full textbeam-chunk
      text/plain1 KBdoc:beam/20f0272f-7b57-4162-9e25-c21ae614367b
      Show excerpt
      train_text, test_text, train_labels, test_labels = train_test_split(df['text'], df['label'], test_size=0.2, random_state= 42) # Load a pre-trained multi-language model model_name = 'distilbert-base-multilingual-cased' tokenizer = AutoToken
  2. ctx:claims/beam/e8aa5db9-3e5f-4e4b-b042-f2179d9b2b8f

See also

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