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We study methods for automated parsing of informal mathematical expressionsinto formal ones, a main prerequisite for deep computer understanding ofinformal mathematical texts. We propose a context-based parsing approach thatcombines efficient statistical learning of deep parse trees with their semanticpruning by type checking and large-theory automated theorem proving. We showthat the methods very significantly improve on previous results in parsingtheorems from the Flyspeck corpus.

Semantic Parsing of Mathematics by Context-based Learning from Aligned Corpora and Theorem Proving