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Type or paste a Danish text into the input box above.
Select a POS analyzer from the left column, then click the "Go" button.
| Example Danish Text for POS Analysis |
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Apple overvejer at købe et britisk startup for 1 milliard dollar.
Selvkørende biler flytter forsikringsansvaret over på producenterne.
San Francisco overvejer at forbyde udbringningsrobotter på fortovet.
London er en storby i Storbritannien.
Hvor er du?
Hvem er Frankrings president?
Hvad er hovedstaden i USA?
Hvornår blev Barack Obama født?
A part of speech is a category that describes the role a word plays in a sentence.
Improving Danish language learning using Part-of-Speech (POS) tagging involves leveraging syntactic and morphological information to understand sentence structure, disambiguate word meanings, and master inflectional rules.
- Danish Part-of-Speech
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UPOS of Danish
UPOS (Universal POS) is a Coarse-grained and simplified tag that work consistently across all languages. They are shown in the following format.
Headword lemma UPOS DEP 👤NER
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XPOS of Danish
XPOS (Detailed POS) is a Fine-Grained tag specific to the Danish language and the Danish training data. They are shown in the following format.
Headword lemma XPOS DEP 👤NER
Headword : Headwords are displayed in bold.
lemma : The dictionary form or "root" of a Danish word. It removes grammatical variations. The lemma is only displayed if the headword is not equal to the lemma.
UPOS : Universal Part-of-Speech. A coarse-grained, standardized tag (like NOUN, VERB, or ADJ) designed to work across all human languages. See examples
XPOS : Language-Specific Part-of-Speech. A fine-grained tag specific to a particular Danish language’s grammar (e.g., distinguishing a plural noun from a singular noun, etc). See examples
DEP : Dependency. The grammatical relationship between words. It shows how words depend on one another, such as identifying which word is the subject (nsubj) or the direct object (obj). See examples
👤NER : Named Entity Recognition. The identification of ""real-world"" entities within the text, such as People (PER), Locations (GPE), Organizations (ORG), or Dates. See examples
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