I am working on a project of "AUTOMATED ESSAY EVALUATION". There will be an student answer and a standard/model answer. These two answers are formatted into a standard format. Thereafter these two formats are compared. According to the matching evaluation will be done. I am wondering how to transform english sentence into the standard format like FOPL, Object oriented format, associative network, frame structure etc.
As others have commented, there is currently no general solution to this problem but there is existing best practice.
There has been lots of research in this area. I would characterize this as straddling the line between computational linguistics, artificial intelligence, and education/testing theory. For example, a recent text on the subject is Shermis and Burnstein's Automated Essay Scoring: A Cross-disciplinary Perspective. So this question is actually incredibly broad in scope.
There are also existing systems that perform such analysis, notably ETS's Criterion system. A complete description of that system can be found in the Association for Advancement of Artificial Intelligence site. The approach is a little different than what you seem to assume in your question. It is statistical in nature; it doesn't parse the grammatical structure of the essays but rather compares characteristics of the essays to corpora of common bigrams (2-word strings) and essays with known scores. Analysis and scoring is performed using AI decision-making and voting algorithms.