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Semantic parsing is the task of converting a natural language utterance to a logical form: a machine-understandable representation of its meaning. [1] Semantic parsing can thus be understood as extracting the precise meaning of an utterance.
Some parser generators, such as the byacc-derived BtYacc ("Backtracking Yacc"), give the generated parser the ability to try multiple attempts to parse the tokens. In the problem described here, if an attempt fails because of semantic information about the identifier, it can backtrack and attempt other rules.
Semantic analysis or context sensitive analysis is a process in compiler construction, usually after parsing, to gather necessary semantic information from the source code. [1] It usually includes type checking , or makes sure a variable is declared before use which is impossible to describe in the extended Backus–Naur form and thus not ...
A more complex example is the lexer hack in C, where the token class of a sequence of characters cannot be determined until the semantic analysis phase since typedef names and variable names are lexically identical but constitute different token classes. Thus in the hack, the lexer calls the semantic analyzer (say, symbol table) and checks if ...
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.
Semantic analysis usually requires a complete parse tree, meaning that this phase logically follows the parsing phase, and logically precedes the code generation phase, though it is often possible to fold multiple phases into one pass over the code in a compiler implementation.
Some variations of formal semantics include the following: Action semantics [9] is an approach that tries to modularize denotational semantics, splitting the formalization process in two layers (macro and microsemantics) and predefining three semantic entities (actions, data and yielders) to simplify the specification;
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 ...