Generating training data for machine learning

A computer program product comprising one or more computer readable storage media and program instructions stored on said one or more computer readable storage media, said program instructions comprising instructions to:

• receive a rule, wherein said rule comprises at least one token;
• receive at least two dictionaries, wherein said at least two dictionaries comprise at least one general language dictionary and at least one domain-specific dictionary for a domain;
• for each of said at least one token, select at least one word at random from at least one of said at least two dictionaries and add said at least one word to a test data line, such that said test data line comprises a candidate statement conforming to said rule;
• filter said candidate statement based on a domain-specific model for said domain;
• and
• include said candidate statement in training data provided to a machine learning model.

A computer system comprising:

• one or more processors;
• one or more computer readable storage media;
• computer program instructions;
• said computer program instructions being stored on said one or more computer readable storage media;
• said computer program instructions comprising instructions to:
• receive a rule, wherein said rule comprises at least one token;
• receive at least two dictionaries, wherein said at least two dictionaries comprise at least one general language dictionary and at least one domain-specific dictionary for a domain;
• for each of said at least one token, select at least one word at random from at least one of said at least two dictionaries and add said at least one word to a test data line, such that said test data line comprises a candidate statement conforming to said rule;
• filter said candidate statement based on a domain-specific model for said domain;
• and
• include said candidate statement in training data provided to a machine learning model.