UDPipe

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Tokenize and annotate text with trained language models

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80/100
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Answers use saved listing facts and recorded sources.

What it does

UDPipe provides a language-processing pipeline for tokenization, grammatical tagging, lemmatization and dependency parsing.

For a local UDPipe 1 job, choose the trained model, UTF-8 input and tokenization, tagging or parsing stages, then send the structured result to standard output or a named file. Output templates and formats have their own controls. The manual says the default loads the whole input before processing; immediate mode processes complete sentence blocks sooner. UDPipe 2 is a separate Python prototype, and both versions are available through a hosted service. The engine's MPL licence does not remove non-commercial or additional conditions attached to supplied language models.

Strengths

  • A complete tokenization-to-parsing pipeline
  • Standalone application and service interfaces

Best for

  • Preparing a corpus for grammatical analysis

Sources