What are syntax and parsing involved in natural language processing?  Question 9Answera.Tokenization, stop words removal, stemming, and lemmatizationb.Labeling each word in a sentence with its grammatical categoryc.Identifying the language of the textd.Generating human-like text

The question asks about the roles of syntax and parsing in natural language processing (NLP).

Syntax in NLP refers to the arrangement of words in a sentence to make grammatical sense. It involves rules and principles that guide how we organize words into meaningful sentences. Syntax analysis, also known as parsing, is used to analyze a sentence based on grammar, and it forms a part of many NLP tasks.

Parsing in NLP is the process of analyzing a string of symbols, either in natural language or in computer languages, according to the rules of a formal grammar. In NLP, parsing involves taking input data (a sentence, for example), and building a parse tree (a data structure that encapsulates the hierarchical structure of the sentence).

From the options provided:

a. Tokenization, stop words removal, stemming, and lemmatization are all preprocessing steps in NLP, not specifically related to syntax and parsing.

b. Labeling each word in a sentence with its grammatical category is a part of syntactic analysis and is done during parsing. This process is known as Part-of-Speech (POS) tagging.

c. Identifying the language of the text is a separate task in NLP, not directly related to syntax and parsing.

d. Generating human-like text is a higher-level task in NLP, often achieved through methods like text generation algorithms and it uses parsing and syntax as part of its process, but it's not specifically about syntax and parsing.

So, the most accurate answer to the question would be option b. Labeling each word in a sentence with its grammatical category.