import nltk
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.probability import FreqDist

nltk.download('punkt_tab')
nltk.download('stopwords')
nltk.download('averaged_perceptron_tagger')
nltk.download('averaged_perceptron_tagger_eng')

text = "natural language processing makes computer understand human language"

tokens = word_tokenize(text)
print("Tokens: ",tokens)

stop_words = set(stopwords.words('english'))
filtered_words = [word for word in tokens if word.lower() not in stop_words]
print("Filtered words: ",filtered_words)

freq_dist = FreqDist(filtered_words)
print("Word Frequency: ",freq_dist)

pos_tags = nltk.pos_tag(tokens)
print("POS Tags:",pos_tags)