Semantic role labeling

<p>In <a href="/facts/Natural_language_processing/1hjMKsSN">natural language processing</a>, semantic role labeling (also called <a href="/facts/Semantic_parsing/VEwJ18nL">shallow semantic parsing</a> or slot-filling) is the process that assigns labels to words or phrases in a sentence that indicates their <a href="/facts/Semantic_role/T57IHVuS">semantic role</a> in the sentence, such as that of an <a href="/facts/Agent_(grammar)/EyraFmNd">agent</a>, goal, or result.
</p><p>It serves to find the meaning of the sentence. To do this, it detects the arguments associated with the <a href="/facts/Predicate_(grammar)/v1hK1EL2">predicate</a> or <a href="/facts/Verb/zp42buvn">verb</a> of a <a href="/facts/Sentence_(linguistics)/GhKKkcm2">sentence</a> and how they are classified into their specific <a href="/facts/Thematic_relation/T57IHVuS">roles</a>. A common example is the sentence "Mary sold the book to John." The agent is "Mary," the predicate is "sold" (or rather, "to sell,") the theme is "the book," and the recipient is "John." Another example is how "the book belongs to me" would need two labels such as "possessed" and "possessor" and "the book was sold to John" would need two other labels such as theme and recipient, despite these two clauses being similar to "subject" and "object" functions.
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Semantic role labeling open-in-new

Semantic role labeling