NLP-Lecture 4 Part-Of-Speech Tagging_part of speech tagging

Learning Objective

• Part-of-Speech Tags
• Part-of-Speech Tagging
• • Simple Statistic Models
• • Sequence Labeling Models: Hidden Markov Model (HMM)
• • Maximum Entropy Markov Model (MEMM)
• • Conditional Random Fields (CRF)

Part-of-Speech Tagging

Introduction to Part-Of-Speech (POS) Tagging

• Part-of-Speech (for short POS) is the name for a group words, which have similar grammatical functions, such as noun, verb, pronoun, proposition, adverb, conjunction, participle and article.
• • They are also known as syntactic classes(句法类别序列).
• A semantic class associates to the general meaning, such as human, animal and plant.
• Part-of-Speech tagging is a task of assigning a part-of-speech tag (like noun, verb, adjectives) to each word in a sentence. In such labelings, parts of speech are generally represented by placing the tag after each word, delimited by a slash.

• Part-of-speech tagging is the process of assigning a part-of-speech marker to each word in an input text.3
  The input to a tagging algorithm is a sequence of (tokenized) words and a tagset, and the output is a sequence of tags, one per token.

• Tagging is a disambiguation task; words are