Our lemmatization software helps to disambiguate and group words by considering the context.
Let’s take the word book as an example: depending on the surrounding text it can mean two different things.
I enjoy booking my trips online, it helps me to save money: In this case, booking means reservation, the lemma being the verb “book”.
I bought three new books last week on my trip to Dublin: In this case, books refers to a novel, the lemma being the noun “book”.
If the algorithm can treat each of those “book” as different words, the error margin will be lower, therefore, we will increase the accuracy of the results even when using a smaller training corpora.
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