Abstract: Systems and methods for determining confidence levels associated with attribute values of informational objects. An example method comprises: receiving a natural language text; performing syntactico-semantic analysis of the natural language text to produce a plurality of semantic structures; interpreting the plurality of semantic structures using a set of production rules to produce a plurality of data items, each data item associating an attribute value with an informational object representing an entity referenced by the natural language text; and determining, for at least one data item of the plurality of data items, a confidence level associated with the attribute value, by evaluating a confidence function associated with the set of production rules.

Abstract: Systems and methods for utilizing user-verified data for training confidence level models.

Abstract: Systems and methods for information extraction using alternative variants of syntactico-semantic analysis. An example method comprises: performing a syntactico-semantic analysis of at least part of a natural language text to produce a plurality of syntactico-semantic structures representing the part of the natural language text, wherein the plurality of syntactico-semantic structures comprises a first alternative syntactico-semantic structure and a second alternative syntactico-semantic structure; merging the plurality of syntactico-semantic structures to produce a merged syntactico-semantic structure; and identifying, within the part of the natural language text, one or more information objects by interpreting the merged syntactico-semantic structure to associate one or more tokens comprised by the part of the natural language text with a category of information objects.

Abstract: Systems and methods for determining confidence levels associated with attribute values of informational objects. An example method comprises: receiving a natural language text; performing syntactico-semantic analysis of the natural language text to produce a plurality of semantic structures; interpreting the plurality of semantic structures using a set of production rules to produce a plurality of data items, each data item associating an attribute value with an informational object representing an entity referenced by the natural language text; and determining, for at least one data item of the plurality of data items, a confidence level associated with the attribute value, by evaluating a confidence function associated with the set of production rules.