The phrase in the hierarchy of language units Contents Introduction

2.1 A hierarchical analysis of sentences into their constituent parts gives us a better understanding of the relationship among them. Functional grammar relates grammatical catagories to the communicative functions which they serve. These functions are seen to operate at different levels of organization in the language. This implies segmental principle of organization, in which larger units may be seen as being formed from smaller units and smaller units being combined to form the larger units. It can be seen from the above analysis that words and groups perform different functions at different levels. A group, at times, functions as a word. Sometimes addition of a morpheme ‘en’ causes a word to behave in a way which is quite different to its characteristic behaviour of the class to which it belongs, .e.g., the word sunken. The phenomenon whereby a group actually functions as a word is known as Rankshift or Embedding. This means that a unit of a certain complexity behaves in terms of its function in the total structure of the sentence as if it were a unit of a “lower” rank. Rankshift embedding is very common in English language, and there are many instances where groups of words may function as a single item. There are many phrases such as “out- of- the way”,”ready -to- wear”, “made to measure” etc. which can be interpreted as single items. There are many approaches to grammar. The prescriptive approach to grammar categorizes words into different classes. The descriptive approach attempts to describe the regular structures of the language as it is used, not according to some point of view of how it should be used. It is the descriptive approach to grammar which has led the grammarians to concentrate on the functions performed by different structures in a sentence.Having a better understanding of the functions of different structures in a sentence, helps us improve our grammatical competence which in turn improves the communicative competence of a speaker. Functional grammar hence, a key to communicative success. “Communicative competence can be defined, in terms of three components, as the ability to use the L2 accurately, appropriately, and flexibly. The first component is grammatical competence which involves the accurate use of words and structures in the L2.” .Sentence (8) is ungrammatical: it has three subject nouns but only two verbs. Perhaps surprisingly, readers rate it as more acceptable [47,48] and process the final (object) noun more quickly [49], compared with the correct variant in (9). Presumably, this is because of the large linear distance between the early nouns and the late verbs, which makes it hard to keep all nouns in memory [48]. Results from SRT learning [45], providing a sequence-based analogue of this effect, show that the processing problem indeed derives from sequence – memory limitations and not from referential difficulties. Interestingly, the reading-time effect did not occur in comparable German sentences, possibly because German speakers are more often exposed to sentences with clause – final verbs [49]. This grammaticality illusion, including the cross-linguistic difference, was explained using an RNN model [50].It is well known that sentence comprehension involves the prediction of upcoming input and that more predictable words are read faster [51]. Word predictability can be quantified by probabilistic language models, based on any set of structural assumptions. Comparisons of RNNs with models that rely on hierarchical structure indicate that the non-hierarchical RNNs predict general patterns in reading times more accurately [52 – 54], suggesting that sequential structure is more important for predictive processing. In support of this view, individuals with higher ability to learn sequential structure are more sensitive to word predictability [55]. Moreover, the ability to learn non- adjacent dependency patterns in an SRT task is positively correlated with performance in on-line comprehension of sentences with long-distance dependencies [56].An increasing number of computational linguists have shown that complex linguistic phenomena can be learned by employing simple sequential statistics from human generated text corpora. Such phenomena had, for a long time, beenconsidered parade cases in favour of hierarchical sentence structure. For example, the phenomenon known as auxiliary fronting was assumed to be unlearnable without taking hierarchical dependencies into account [57]. If sentence (10) is turned into a yes – no question, the auxiliary is is fronted, resulting in sentence (11).