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.
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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.