Parsing is the process of analyzing a body of text in order to create a structured representation of its components. In the context of text analytics, Parsing typically refers to the process of extracting information from unstructured text data in order to better understand its meaning.
Parsing can be used for a variety of purposes, including sentiment analysis, topic modeling, and named entity recognition. Depending on the application, different types of Parsing may be used. For example, syntactic Parsing focuses on the structure of sentences, while semantic Parsing focuses on the meaning of words and phrases.
Parsing and Other Terms
Parsing is often confused with other similar terms, such as lemmatization, stemming, and tokenization. However, these terms refer to different processes. Lemmatization is the process of grouping together different inflected forms of a word, such as “run”, “runs”, and “ran”. Stemming is the process of reducing a word to its stem, which is the part of the word that remains after all the affixes have been removed. For example, the stem of “running” is “run”. Tokenization is the process of breaking a body of text up into smaller units called tokens.
While Parsing can be used as a stand-alone text analysis technique, it is often used in combination with other methods, such as natural language processing (NLP) and machine learning.
Syntactic vs Semantic parsing
There are two main types of parsing: syntactic and semantic. Syntactic parsing focuses on the structure of sentences, while semantic parsing focuses on the meaning of words and phrases.
Syntactic parsing is often used to determine the grammatical function of words in a sentence. For example, a syntactic parser might analyze the following sentence: “The dog chased the cat”.
In this sentence, “dog” is the subject, “cat” is the object, and “chased” is the verb. This type of analysis can be useful for tasks such as part-of-speech tagging and dependency parsing.
Semantic parsing, on the other hand, focuses on the meaning of words and phrases. For example, a semantic parser might analyze the following sentence: “The dog chased the cat”.
In this sentence, “dog” is a noun, “cat” is a noun, and “chased” is a verb. This type of analysis can be useful for tasks such as named entity recognition and sentiment analysis.