UralicNLP.net

Download models

Before using the library, you will need to download the models for each language.

var nlp = new UralicApi(); nlp.Download("fin");

Just pass the 3-letter ISO code to the Download function. You can find a list of supported languages in the model catalog

Morphological analysis

You can analyze words' morphology like this

var nlp = new UralicApi(); var analyses = nlp.Analyze("voita", "fin"); foreach (var analysis in analyses){ Console.WriteLine(analysis.ToString()); }

Analyze takes in a word form and a language code. It returns a list of Result objects. The output of the previous code is:

vuo+N+Pl+Par voi+N+Sg+Par voi+N+Pl+Par voittaa+V+Act+Ind+Prs+ConNeg voittaa+V+Act+Imprt+Prs+ConNeg+Sg2 voittaa+V+Act+Imprt+Sg2 voitaa+V+Act+Ind+Prs+ConNeg voitaa+V+Act+Imprt+Prs+ConNeg+Sg2 voitaa+V+Act+Imprt+Sg2

Lemmatization

Sometimes you only want to lemmatize words.

var nlp = new UralicApi(); var analyses = nlp.Lemmatize("voita", "fin"); foreach (var analysis in analyses){ Console.WriteLine(analysis); }

This outputs:

vuo voi voittaa voitaa

For compounds, it is possible to mark the word boundaries:

var nlp = new UralicApi(); var analyses = nlp.Lemmatize("luutapiiri", "fin", true); foreach (var analysis in analyses){ Console.WriteLine(analysis); }

Output:

luu|tapiiri luuta|piiri

Generation

You can also inflect words given their lemma and morphology

var nlp = new UralicApi(); var analyses = nlp.Generate("koira+N+Sg+Par", "fin"); foreach (var analysis in analyses){ Console.WriteLine(analysis.ToString()); }

Output:

koiraa

Tokenization

You can tokenize text like this:

var tokenizer = new Tokenizer(); var text = "An example sentence. Another, super cool sentence!"; var tokens = tokenizer.Tokenize(text); foreach (var sentence in tokens) { foreach (var word in sentence) { Console.Write(word + " "); } Console.WriteLine(); }

Output:

An example sentence . Another , super cool sentence !

If you want to only do sentence or word tokenization, you can use Tokenizer.Sentences("text") and Tokenizer.Words("text") respectively