Lecture

Advanced Natural Language Processing Techniques with NLTK

In this lesson, we will explore advanced features such as POS tagging, named entity recognition, and syntax parsing using NLTK.


1. Part-of-Speech Tagging

A part of speech (POS) refers to the grammatical role of a word in a sentence.

For example, in "I am a student.", I is a pronoun, am is a verb, a is an article, and student is a noun.

POS tagging involves analyzing each word in a sentence to determine its part of speech.

POS Tagging Example
import nltk from nltk.tokenize import word_tokenize from nltk import pos_tag nltk.download('averaged_perceptron_tagger') text = "NLTK provides powerful NLP tools." tokens = word_tokenize(text) tagged = pos_tag(tokens) print(tagged)

In the above code, NNP (proper noun), VBZ (verb, 3rd person singular present), JJ (adjective), etc., are the tags for each word indicating its part of speech.


2. Named Entity Recognition (NER)

Named Entity Recognition (NER) is the process of identifying specific entities such as people, organizations, and locations in a text.

Named Entity Recognition Example
import numpy from nltk.chunk import ne_chunk nltk.download('maxent_ne_chunker') nltk.download('words') sentence = "I live in California." tokens = word_tokenize(sentence) tagged = pos_tag(tokens) ner_tree = ne_chunk(tagged) print(ner_tree)

The output appears as follows:

(S I/PRP live/VBP in/IN (GPE California/NNP) ./.)

Here, GPE indicates a geopolitical entity, and NNP signifies a proper noun.


How About Other Languages?

NLTK is primarily an English-based natural language processing library, so its support for languages like Korean is limited.

For processing languages like Korean, it's common to use libraries such as spaCy or KoNLPy alongside NLTK.

KoNLPy Example
from konlpy.tag import Okt okt = Okt() text = "Python makes natural language processing easy." print(okt.morphs(text)) # Morphological analysis print(okt.nouns(text)) # Extracting nouns print(okt.pos(text)) # POS tagging

With this code, you can separate morphemes and tag parts of speech in a Korean sentence.

While NLTK is excellent for English natural language processing, using other libraries is advisable for handling languages like Korean.


References

Mission
0 / 1

Which of the following words is most appropriate for the blank?

Part-of-speech tagging is the process of analyzing the of each word.
meaning
grammatical role
sentence structure
form

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