  Natural Language Processing (NLP) research has traditionally been
predominantly focused on English, driven by the availability of resources, the
size of the research community, and market demands. Recently, there has been a
noticeable shift towards multilingualism in NLP, recognizing the need for
inclusivity and effectiveness across diverse languages and cultures.
Monolingual surveys have the potential to complement the broader trend towards
multilingualism in NLP by providing foundational insights and resources
necessary for effectively addressing the linguistic diversity of global
communication. However, monolingual NLP surveys are extremely rare in
literature. This study fills the gap by introducing a method for creating
systematic and comprehensive monolingual NLP surveys. Characterized by a
structured search protocol, it can be used to select publications and organize
them through a taxonomy of NLP tasks. We include a classification of Language
Resources (LRs), according to their availability, and datasets, according to
their annotation, to highlight publicly-available and machine-actionable LRs.
By applying our method, we conducted a systematic literature review of Greek
NLP from 2012 to 2022, providing a comprehensive overview of the current state
and challenges of Greek NLP research. We discuss the progress of Greek NLP and
outline encountered Greek LRs, classified by availability and usability. As we
show, our proposed method helps avoid common pitfalls, such as data leakage and
contamination, and to assess language support per NLP task. We consider this
systematic literature review of Greek NLP an application of our method that
showcases the benefits of a monolingual NLP survey. Similar applications could
be regard the myriads of languages whose progress in NLP lags behind that of
well-supported languages.
