Part-of-Speech Tagging
Part-of-speech taggingPOS tagging is the process of classifying and labeling words in a sentence. It is the process of assigning a part-of-speech tag to each word based on the components it plays in syntactic structure or language morphology.
That is, the process of determining whether each word in a sentence is a noun, verb, adjective or other part of speech is also called part-of-speech tagging or simply tagging.
Part-of-speech tagging is a basic task in natural language processing and is used in speech recognition, information retrieval, and many other fields of natural language processing.
Word Classification
Words can be divided into two main categories:
- Content words: nouns, verbs, adjectives, state words, distinguishing words, numerals, quantifiers, pronouns
- Function words: adverbs, prepositions, conjunctions, auxiliary words, onomatopoeia, and interjections.
Part-of-speech tagging refers to the process of marking a correct part of speech for each word in the word segmentation result, that is, the process of determining the part of speech of each word.
Methods for implementing part-of-speech tagging:
It can be mainly divided into rule-based and statistical-based methods.
(1) Part-of-speech tagging based on maximum entropy
(2) Output part of speech based on statistical maximum probability
(3) Part-of-speech tagging based on HMM
Application of part-of-speech tagging:
(1) Syntactic analysis preprocessing
(2) Vocabulary acquisition preprocessing
(3) Information extraction preprocessing
Part-of-speech tagging and others
(1) Part-of-speech tagging is essentially a sequence tagging problem, or more specifically, a classification problem.
(2) Part-of-speech tagging and Chinese word segmentation are closely related and can be combined in two ways.
- Pipeline: Segment first, then tag
- Joint Model: word segmentation and tagging are performed simultaneously