Dilek Zeynep Hakkani-Tür, Murat Saraçlar, Gökhan Tür, Kemal Oflazer and Deniz Yuret. 2018. In
Turkish Natural Language Processing, Kemal Oflazer and Murat Saraçlar (Eds.), Ch.3, pp.53-68. Springer. (
URL)
Abstract: Morphological disambiguation is the task of determining the contextually
correct morphological parses of tokens in a sentence. A morphological disambiguator
takes in sets of morphological parses for each token, generated by a morphological
analyzer, and then selects a morphological parse for each, considering statistical
and/or linguistic contextual information. This task can be seen as a generalization
of the part-of-speech (POS) tagging problem for morphologically rich languages.
The disambiguated morphological analysis is usually crucial for further processing
steps such as dependency parsing. In this chapter, we review morphological disambiguation
problem for Turkish and discuss approaches for solving this problem as
they have evolved from manually crafted constraint-based rule systems to systems
employing machine learning.
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