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rule based machine translation

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Hi friend today let us know about rule based machine translation.this one of  approaches of machine translation and this is  earliest machine translation approach
Rule-based machine translation (RbMT) refers to a machine translation engine built on algorithms that analyze the syntax of the source language and uses rules to transfer the meaning to the target language by building a sentence. 
The rule based machine translation systems are developed  in early 1970’s they are
-Systran
-Japanese mt
-eurotra
At present following companies using  rule based machine translation are
-Apertium
-GramTrans
 The RBMT is based on linking structure  of given input with structure of demanded output service necessarily preserving their unique meaning.
For this process we need following
-          A dictionary that will map every world of source language to target language
-          Rules representing regular source sentence structure
-          Rules representing  target  sentence structure

The rgbt system contains following
·          SL morphological analyzer - analyses a source language word and provides the morphological information;
·          SL parser - is a syntax analyzer which analyses source language sentences;
·          translator - used to translate a source language word into the target language;
·          TL morphological generator - works as a generator of appropriate target language words for the given grammatical information;
·          TL parser - works as a composer of suitable target language sentences;
·         Several dictionaries - more specifically a minimum of three dictionaries:
a SL dictionary - needed by the source language morphological analyser for morphological analysis,
a bilingual dictionary - used by the translator to translate source language words into target language words,
a TL dictionary - needed by the target language morphological generator to generate target language words.

Advantages
-No bilingual texts required. Can be used for  translation that don’t have any  no texts in common
-Domain independent .rules will work on most of domains
-No quality ceiling. Every error can be corrected with targeted rule even if triggered case is rare
-Total control. Easy to debug since most of rules are hand written
- Reusability.  the source language analysis and target language generation parts can be shared between multiple translation systems, requiring only the transfer step to be specialized.
 Disadvantages
-          Unavailability of really  good dictionaries
-          Some linguistic information still needs to be set manually.
-          It is hard to deal with rule interactions in big systems, ambiguity, and idiomatic expressions.

-           Failure to adopt new domains
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