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Shallow semantic parsing is concerned with identifying entities in an utterance and labelling them with the roles they play. Shallow semantic parsing is sometimes known as slot-filling or frame semantic parsing, since its theoretical basis comes from frame semantics, wherein a word evokes a frame of related concepts and roles.
Deep linguistic processing is a natural language processing framework which draws on theoretical and descriptive linguistics.It models language predominantly by way of theoretical syntactic/semantic theory (e.g. CCG, HPSG, LFG, TAG, the Prague School).
In natural language processing, semantic role labeling (also called shallow semantic parsing or slot-filling) is the process that assigns labels to words or phrases in a sentence that indicates their semantic role in the sentence, such as that of an agent, goal, or result. It serves to find the meaning of the sentence.
Part-of-speech tagging (which resolves some semantic ambiguity) is a related problem, and often a prerequisite for or a subproblem of syntactic parsing. Syntactic parses can be used for information extraction (e.g. event parsing, semantic role labelling, entity labelling) and may be further used to extract formal semantic representations.
A Karaka Based Approach to Parsing of Indian Languages; Google AI Blog: SLING: A Natural Language Frame Semantic Parser; DFG Collaborative Research Centre 991: The Structure of Representations in Language, Cognition, and Science; Frame Semantics for Text Understanding by Charles J. Fillmore and Collin F. Baker, 2001
Combinatory categorial grammar (CCG) is an efficiently parsable, yet linguistically expressive grammar formalism.It has a transparent interface between surface syntax and underlying semantic representation, including predicate–argument structure, quantification and information structure.
A notable example of deep semantic annotation is the Groningen Meaning Bank, developed at the University of Groningen and annotated using Discourse Representation Theory. An example of a shallow semantic treebank is PropBank , which provides annotation of verbal propositions and their arguments, without attempting to represent every word in the ...
In machine learning, semantic analysis of a text corpus is the task of building structures that approximate concepts from a large set of documents. It generally does not involve prior semantic understanding of the documents. Semantic analysis strategies include: Metalanguages based on first-order logic, which can analyze the speech of humans.