Analyzing the grammatical structure of sentences, including techniques like dependency parsing and constituency parsing.
Regular Expressions: A pattern-based engine used to match and manipulate text.
Context-Free Grammars: A formal language model that defines the rules for constructing sentences or phrases in a language.
Syntax Trees: A hierarchical representation of a sentence's structure.
Dependency Parsing: Identifying the grammatical relationships between words in a sentence.
Part-of-Speech Tagging: Labeling the parts of speech (nouns, verbs, adjectives, etc.) of words in a sentence.
Named Entity Recognition: Identifying and classifying named entities (people, places, organizations, etc.) in a sentence.
Chunking: Identifying and grouping related words in a sentence.
Phrase Structure Grammars: A type of context-free grammar that describes the structure of phrases in a language.
Lexical Analysis: Identifying the individual words and their properties in a sentence.
Recursive Descent Parsing: A top-down parsing technique that uses a set of recursive procedures to analyze a sentence's structure.
Earley Parsing: A general parsing algorithm that can handle any context-free grammar and is based on dynamic programming.
Natural Language Understanding (NLU): The process of extracting meaning from natural language text.
Semantics: The study of meaning in language.
Ambiguity Resolution: Resolving the multiple possible interpretations of ambiguous sentences.
Statistical Parsing: Using machine learning techniques to automatically learn how to parse text.
Constituent Parsing: Identifying constituents (noun phrases, verb phrases, etc.) in a sentence.
Probabilistic Parsing: Using statistical probabilities to choose the best parse for a sentence.
Parsing Algorithms: Different algorithms used to parse natural language text, including LL, LR, CYK, and Earley.
Parsing Complexity: Measuring the time and space complexity of different parsing algorithms.
Error Handling: Dealing with errors and uncertainties in the parsing process.
lexing or tokenization: The process of breaking the input text into words or tokens to allow for further processing.
syntax parsing: The process of analyzing the structure of a sentence to determine its grammatical structure.
semantic parsing: The process of analyzing the meaning of a sentence by mapping words to their corresponding concepts and forming a logical representation of the sentence.
dependency parsing: The process of analyzing the relationships between words in a sentence to form a tree-like structure.
constituency parsing: The process of dividing a sentence into its constituent parts, such as nouns, verbs, and phrases.
shallow parsing or chunking: The process of identifying meaningful groups of words in a sentence, such as noun phrases or verb phrases.
statistical parsing: The process of using statistical models to determine the most likely parse of a sentence.
rule-based parsing: The process of using a pre-defined set of rules to parse a sentence.
hybrid parsing: The process of combining multiple parsing techniques to achieve more accurate results.
chart parsing: The process of using dynamic programming to build and store parse trees as a series of smaller, overlapping sub-trees.