EXTRACTING INFORMATION FROM STRUCTURED DOCUMENTS COMPRISING NATURAL LANGUAGE TEXT

1 . A method, comprising:

receiving, by a processing device, a table comprising a natural language text;

identifying, within the table, a header and a plurality of cells organized into rows and columns;

performing semantico-syntactic analysis of the natural language text to produce a plurality of semantic structures;

interpreting the plurality of semantic structures using a first set of production rules to produce a data object representing the table;

analyzing the header to identify a plurality of ontology classes associated with respective table columns; and

modifying the data object representing the table using a second set of production rules associated with the ontology classes associated with the table columns.

2 . The method of claim 1 , wherein the data object is represented by a Resource Definition Framework (RDF) graph.

3 . The method of claim 1 , wherein modifying the data object representing the table comprises enhancing the initial RDF graph by performing at least one of: adding a new object or adding a new relationship.

4 . The method of claim 1 , wherein each semantic structure of the plurality of semantic structures is represented by a graph comprising a plurality of nodes corresponding to a plurality of semantic classes and a plurality of edges corresponding to a plurality of semantic relationships.

5 . The method of claim 1 , wherein a production rule of a first set of production rules comprises one or more logical expressions defined on one or more semantic structure templates.

6 . The method of claim 1 , wherein a production rule of a second set of production rules comprises one or more logical expressions defined on one or more semantic structure templates.

7 . The method of claim 1 , wherein analyzing the header is performed by using an auxiliary ontology comprising a plurality of classes associated with a document structure.

8 . A system, comprising:

a memory;

a processor, coupled to the memory, the processor configured to:

receive a table comprising a natural language text;

identify, within the table, a header and a plurality of cells organized into rows and columns;

perform semantico-syntactic analysis of the natural language text to produce a plurality of semantic structures;

interpret the plurality of semantic structures using a first set of production rules to produce a data object representing the table;

analyze the header to identify a plurality of ontology classes associated with respective table columns; and

modify the data object representing the table using a second set of production rules associated with the ontology classes associated with the table columns.

9 . The system of claim 8 , wherein the data object is represented by a Resource Definition Framework (RDF) graph.

10 . The system of claim 8 , wherein modifying the data object representing the table comprises enhancing the initial RDF graph by performing at least one of: adding a new object or adding a new relationship.

11 . The system of claim 8 , wherein each semantic structure of the plurality of semantic structures is represented by a graph comprising a plurality of nodes corresponding to a plurality of semantic classes and a plurality of edges corresponding to a plurality of semantic relationships.

12 . The system of claim 8 , wherein a production rule of a first set of production rules comprises one or more logical expressions defined on one or more semantic structure templates.

13 . The system of claim 8 , wherein a production rule of a second set of production rules comprises one or more logical expressions defined on one or more semantic structure templates.

14 . The system of claim 8 , wherein analyzing the header is performed by using an auxiliary ontology comprising a plurality of classes associated with a document structure.

15 . A computer-readable non-transitory storage medium comprising executable instructions that, when executed by a computing device, cause the computing device to perform operations comprising:

receiving a table comprising a natural language text;

identifying, within the table, a header and a plurality of cells organized into rows and columns;

performing semantico-syntactic analysis of the natural language text to produce a plurality of semantic structures;

interpreting the plurality of semantic structures using a first set of production rules to produce a data object representing the table;

analyzing the header to identify a plurality of ontology classes associated with respective table columns; and

modifying the data object representing the table using a second set of production rules associated with the ontology classes associated with the table columns.

16 . The computer-readable non-transitory storage medium of claim 15 , wherein the data object is represented by a Resource Definition Framework (RDF) graph.

17 . The computer-readable non-transitory storage medium of claim 15 , wherein modifying the data object representing the table comprises enhancing the initial RDF graph by performing at least one of: adding a new object or adding a new relationship.

18 . The computer-readable non-transitory storage medium of claim 15 , wherein each semantic structure of the plurality of semantic structures is represented by a graph comprising a plurality of nodes corresponding to a plurality of semantic classes and a plurality of edges corresponding to a plurality of semantic relationships.

19 . The computer-readable non-transitory storage medium of claim 15 , wherein a production rule of a first set of production rules comprises one or more logical expressions defined on one or more semantic structure templates.

20 . The computer-readable non-transitory storage medium of claim 15 , wherein a production rule of a second set of production rules comprises one or more logical expressions defined on one or more semantic structure templates.