Fiscal federalism relevant for all kinds of government: unitary, federal and confederal. The concept of fiscal federalism is not to be associated with fiscal decentralization in officially declared federations only; it is applicable even to non-federal states (having no formal federal constitutional arrangement) in the sense that they encompass different levels of government which have de facto decision-making authority. This, however, does not mean that all forms of governments are 'fiscally' federal, only that 'fiscal federalism' is a set of principles that can be applied to all countries attempting 'fiscal decentralization'. In fact, fiscal federalism is a general normative framework for assignment
Word-sense disambiguation space. However, these supervised methods are subject to a new knowledge acquisition bottleneck since they rely on substantial amounts of manually sense-tagged corpora for training, which are laborious and expensive to create. Because of the lack of training data, many word sense disambiguation algorithms use semi-supervised learning, which allows both labeled and unlabeled data. The Yarowsky algorithm was an early example of such an algorithm. It uses the ‘One sense per collocation’ and the ‘One sense per discourse’ properties of human languages for word sense disambiguation. From observation, words tend to exhibit only one sense in most given discourse and