NLP 2

Identifying named entities in a text

Breaking down a text into individual words or tokens

Grouping similar words together

Removing stop words from a text

Noun

Adjective

Verb

Adverb

Identify structure by focusing on the relationships between words

Break down a document into sentences

Extract named entities from a sentence

Classify text into categories

Splitting a text into tokens

Grouping words into predefined categories

Lemmatizing words into their base forms

Identifying the sentiment of a sentence

Stemming

Lemmatization

Stop word removal

Tokenization

Stemming removes stop words, while lemmatization does not

Lemmatization removes affixes to derive the base form of a word, while stemming does not

Stemming removes affixes and produces non-dictionary words, while lemmatization produces dictionary words

Lemmatization is a simpler approach than stemming

Common nouns in a sentence

Punctuation marks

Words that refer to persons, organizations, or locations

The structure of sentences

Linking words to their grammatical categories

Connecting named entities in text to a knowledge base

Grouping synonyms together

Removing irrelevant entities from the text

Breaking a text into individual words

Identifying and extracting named entities

Dividing a text into individual sentences

Grouping words into meaningful phrases

"rain"

"John"

"the"

"quick"