This paper deals with adaptive rule based machine translation from English to Telugu. This approach is based on rule-based methodologies. If-then methods to select the best rules for target language in translation, Probability based appropriate word selection for a given sentence and rough sets to classify a given sentence are the approaches used in this technique. Set of production rules of English and Telugu, Training set and Dictionary for both the languages are developed for this purpose. User gives and input, which is an English sentence. The given input sentence is then tokenized into individual words. These words are tagged with their respective parts of speech. All other words that are not found in the pre-defined database are tagged using grammatical rules that are formulated. Using these POS tags, the respective word translations are retrieved from the database. These individual words are then concatenated to form a sentence that is the result of user's input.

Retrieval according to Events and Times. Our long term intension is to build a system which automatically extracts Events and Time expressions and ordering them in a particular order. Ordering of events become significant task and it is assists to finding all feasible times a given event can occur, all relationships between two given events, finding one or more consistent scenarios and finally representing data in a minimal network form.In this paper, we are focusing about automatic extraction of Quantitative, Qualitative time's information and from Legal Text Documents, along with this Legal text expressed in natural language can be automatically annotated with semantic mark ups using natural language processing Techniques. Finally applied reasoning among temporal information with the help of extracted information. Reasoning can be done using constraint satisfaction networks by applying Allen's Algebra relations. Apart from this result analysis obtained using Precision and Recall statistical measurements over standard dataset DUC 2005.