What specific task in Natural Language Processing involves classifying arguments into semantic roles?

Slot filling

In the context of Natural Language Processing (NLP), slot filling is the designated task focused on linguistic analysis rather than mechanical engineering. This process requires a system to meticulously identify the various arguments that relate to a particular predicate, usually a verb found within a given sentence. Once identified, these arguments—which represent the pieces of information relevant to the action—are then classified into specific semantic roles, thereby structuring unstructured text data into meaningful, labeled components that a computer can process effectively. For instance, in a sentence describing an action, slot filling determines who performed the action (the agent) and what object was acted upon (the instrument or theme).