Global Bilgi RPA (EN)

Turkcell

Turkcell

Aktiviteler

Turkcell Lemma

You can convert incoming texts into root using the Turkcell Lemma service. It can be used before Intent classification and sentiment analysis.

Turkcell Morphology

The Turkcell Morphology service examines the text received in terms of linguistics. It verifies semantically confused verb-noun choices. For example, using this service, we can learn whether the word “meal” in the sentence “Meal is necessary” is a noun or a verb.

Turkcell Normalization

Using the Turkcell Normalization service, it minimizes (deascify) the text sent to it. It also tries to complete corrections that are not suitable for Turkish, such as misspelled words. For example; KITAPLİK > kitaplık

Turkcell Number To Text

The Turkcell Number To Text service converts the numeric values in the text sent to it into written reading.

Turkcell Sentence Bound

If there are sentences in the incoming text, the Turkcell Sentence Bound service tries to divide the text into sentences.

Turkcell Spell Checker

Turkcell Spell Checker service tries to find the correct spelling of the word sent to it. The first return result in the list is the one we expect to be most likely. The correct answer may differ depending on the content.

Turkcell Text To Number

The Turkcell Text To Number service converts the numeric values in the text sent to it into numbers. Here, if the number is written after the text and if the meaning is not lost when the two are read together, that number is included in the previous number.

Turkcell Tokenization

The Turkcell Tokenization service divides the text sent to it into tokens (words and punctuation).

Turkcell Word Segmenter

The Turkcell Word Segmenter service tries to separate the forgotten words that are not separated by spaces in the text sent to it. The first return result in the list is the one we expect to be most likely.

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