Normalizing Text for Machine Learning with Lemmatization

Avoid ambiguity using word context

The same word can have
different meanings depending on the context. The only way of getting accurate results is by the use
of lemmatization.

Higher Accuracy

By using the context of each word.

Multilingual

Available in +100 languages and variants.

High Quality Results

The Bitext lemmatizer outperforms the rest of the lemmatizers as shown in our benchmark.

Easy Customization

Bitext lemmatizer can be easily customized by modifying
or extending the dictionaries,

Whitepaper

Lemmatization vs Stemming: Download to find out the main differences and examples.

 

Benchmark

The report presents a comparison among NLTK, Stanford and Bitext.

Check out the results now!  

Demo

Do you have questions?

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