Automatic construction of arguments

A method comprising using at least one hardware processor for:

• generating a claim training dataset comprising a first content item and multiple claims, each of the multiple claims being with respect to a topic of a plurality of topics, wherein the claims are selected from the first content item by a first group of people;
• generating a classification training dataset comprising a classification of each claim of the multiple claims with respect to its corresponding topic, wherein the classification is performed by a second group of people;
• learning a claim function for extracting claims from a provided content item, with respect to a provided topic, wherein the learning is based on the claim training dataset;
• and
• learning a classification function for classifying a provided claim with respect to a provided topic, wherein the learning is based on the classification training dataset.

A computer program product comprising a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by at least one hardware processor to:

• receive a Topic Under Consideration (TUC);
• provide the TUC as input to a claim function, wherein the claim function is configured to mine at least one content resource, and applying the claim function to the at least one content resource, to extract claims with respect to the TUC;
• and
• provide the TUC as input to a classification function, and applying the classification function to one or more claims of the extracted claims, to output corresponding one or more classification tags, wherein each classification tag is associated with its corresponding claim.