In linguistics, morphology is the study of words, how they are formed, and their relationship to other words in the same language. It analyzes the structure of words and parts of words such as stems, root words, prefixes, and suffixes.

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About Turkish Morphology


Morphological Productivity


Likewise other agglutinative languages, Turkish poses various challenges due to its rich morphological structure. It has both derivational and inflectional suffixes and more than 20,000 valid wordforms can be formed from a single noun root. This property of Turkish results in very large vocabulary sizes and traditional vocabulary based methods that work well for other languages with relatively simpler morphological structures fail to achieve high performance.

Turkish named entity recognition

Morphological Analysis


Morphological analysis is determining the parts of the words, namely morphemes. For some languages such as English, the morphological analysis task is not very complex whereas it is much more complicated for some languages like Turkish, Finnish, Hungarian and Czech. The complicated morphological processes of those languages may end up multiple derivations and/or inflections by the suffixes agglutinated each other, just like the beeds on a string. Therefore, for those languages, morphological analysis is required to have a better understanding of the words, syntactical structure and semantics.

Turkish morphological analysis example

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Morphological Ambiguity

Turkish morphological analysis usually produces multiple possible analysis results, which causes morphological ambiguity. Our deep learning based models handle the morphological disambiguation by considering the context.

Our Turkish Morphological Analysis Module Features


Lightning Fast

Thanks to finite-state-transducers, our morphological analysis module is lightning fast.

Wide Coverage

Although theoretically the set of Turkish wordforms is infinite, we have a very wide coverage.

Disambiguation

Our deep learning based disambiguator identifies the correct morphological parse in the context.

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