Identifying semantic relationships using visual recognition

A system comprising:

• a computer-readable storage medium storing instructions, which, when executed by a processor, is configured to cause the processor to perform a method comprising:
• receiving natural language content;
• determining, by analyzing the natural language content using a natural language processor, a part of speech of respective terms within the natural language content;
• determining a semantic type for each of at least two terms within the natural language content;
• generating a parse tree representation containing a plurality of nodes based on the natural language content, each of the plurality of nodes corresponding to at least one term within the natural language content, wherein visual characteristics of respective nodes of the plurality of nodes within the parse tree representation depend on the part of speech and semantic type of the respective terms;
• and
• generating, by a machine learning model, a bounding box identifying a semantic relationship around a set of nodes on the parse tree representation, the set of nodes including the at least two terms.

A computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processor to cause the processor to perform a method comprising:

• receiving natural language content;
• determining, by analyzing the natural language content using a natural language processor, a part of speech of respective terms within the natural language content;
• determining a semantic type for each of at least two terms within the natural language content;
• generating a parse tree representation containing a plurality of nodes based on the natural language content, each of the plurality of nodes corresponding to at least one term within the natural language content, wherein visual characteristics of respective nodes of the plurality of nodes within the parse tree representation depend on the part of speech and semantic type of the respective terms;
• and
• generating, by a machine learning model, a bounding box identifying a semantic relationship around a set of nodes on the parse tree representation, the set of nodes including the at least two terms.