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Type or paste a Finnish text into the input box above.
Select a POS analyzer from the left column, then click the "Go" button.
| Example Finnish Text for POS Analysis |
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Itseajavat autot siirtävät vakuutusvastuun autojen valmistajille.
San Francisco harkitsee toimitusrobottien liikkumisen kieltämistä jalkakäytävillä.
Lontoo on suuri kaupunki Yhdistyneessä Kuningaskunnassa.
Missä sinä olet?
Mikä on Yhdysvaltojen pääkaupunki?
Kuka on Suomen presidentti?
Milloin Sauli Niinistö on syntynyt?
A part of speech is a category that describes the role a word plays in a sentence.
Improving Finnish 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.
- Finnish Part-of-Speech
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UPOS of Finnish
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 Finnish
XPOS (Detailed POS) is a Fine-Grained tag specific to the Finnish language and the Finnish 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 Finnish 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 Finnish 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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