According to Sinnemäki (2008, 2011), a common problem in defining and understanding complexity is how to measure complexity in a reliable manner. Since there is no unified definition among researchers in the sciences of complexity including linguistics, it can be difficult to understand complexity and the “question of complexity is bound to remain elusive” (Sinnemäki, 2008, 2011). Hence in studying and approaching linguistic complexity, there may be a few points to consider as well as a number of clarifications that should be made such as:

• Complexity is separated from difficulty (Dahl, 2004);
• Complexity is classified in different types (Rescher 1998);
• Local complexity is separated from global complexity (Miestamo 2008);
• Complexity is measured as the description length of an object’s structure (Gell-Mann 1995).

Firstly, Dahl (2004) claims that it is important to keep complexity separated from difficulty as different users experience a different level of difficulty, and perhaps also between different usage events of the same user.

The second point to note is that there is also an unexpected unity behind the different formulations for complexity. To explain this, Lloyd (2001) classifies complexity metrics under three broad types, whereas Rescher (1998) classifies it in only a few modes. This shows that many researchers do agree that there are different notions of complexity. While it is impossible to devise a “correct” metric, it is feasible to approach language complexity by classifying it into different categories.

The third point is that local complexity should be separated from global complexity. Local complexity is about the complexity of some part of an entity, whereas global complexity is about the overall complexity of that similar entity. It is therefore rather impractical to measure the overall complexity of a particular linguistic system, as it is quite impossible to devise a fully comprehensive description of the grammar of any single language (Miestamo 2008). It is, however, both possible and practical to measure the local complexity of a system for example, the complexity of the numeral system, the case system, or the verb’s argument structure (e.g. Sinnemäki 2011).

The last point is complexity is intuitively situated between order and disorder. To put it simply, the general intuition is that when a language has more “structural units/rules/representations” (Hawkins, 2009: 252) in its system, it would be more complex. Since there has been no unified metric system for complexity, the best way to capture this is to measure the length of description of an object’s structure (effective complexity, Gell-Mann 1995) instead of the length of description of the object itself (e.g. Kolmogorov complexity). This is because the latter is usually related to randomness with complexity, while the former, randomness with low complexity.

According to Sinnemäki (2008, 2011), he argued that while it is impossible to compare the overall complexity of one language to that of another, it is possible to compare complexity across languages when focusing on particular types of effective complexity in their local contexts.