You're essentially done. Please make sure you appreciate all the power you learned. You will put it to good use soon. NLP and Finding Characters You will use the power of nltk to find characters in a novel. Write the function find_characters_nlp. It will use nltk. [64] def find_characters_nlp(text, topn): output = [] for sent in nltk.sent_tokenize(text): tagged = n1tk. for chunk in nltk.ne_chunk(tagged): if hasattr(chunk, 'label') and chunk.label() == "PERSON": name = ' '.join(c[0] for c in chunk) print(name) pos_tag(nltk.word_tokenize(sent))
You're essentially done. Please make sure you appreciate all the power you learned. You will put it to good use soon. NLP and Finding Characters You will use the power of nltk to find characters in a novel. Write the function find_characters_nlp. It will use nltk. [64] def find_characters_nlp(text, topn): output = [] for sent in nltk.sent_tokenize(text): tagged = n1tk. for chunk in nltk.ne_chunk(tagged): if hasattr(chunk, 'label') and chunk.label() == "PERSON": name = ' '.join(c[0] for c in chunk) print(name) pos_tag(nltk.word_tokenize(sent))
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
Related questions
Question
Answer the given question with a proper explanation and step-by-step solution.
in Python,
What should I add to get a right list?
You should see these numbers: ('Jim', 336) ('Tom', 150) ('Huck', 41) ('Tom Sawyer', 37) ('Aunt Sally', 37) ('Buck', 32)
I think it is almost done, but not certain how to handle it yet.
Notes:
- note that with nltk, there's no need for stopwords, ngrams
![You're essentially done. Please make sure you appreciate all the power you learned. You will put it
to good use soon.
NLP and Finding Characters
You will use the power of nltk to find characters in a novel. Write the function find_characters_nlp.
It will use n1tk.
[64] def find_characters_nlp(text, topn):
output = []
for sent in nltk.sent_tokenize(text):
tagged = nltk.pos_tag(nltk.word_tokenize (sent))
for chunk in nltk.ne_chunk(tagged):
if hasattr(chunk, 'label') and chunk.label() == "PERSON":
name = ' ¹.join(c[0] for c in chunk)
print (name)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ff8417094-7b6e-4d94-9afb-e6ea08525173%2F0ddeb43e-f0e0-4736-a63c-fb6b8de3a459%2Ft1tnzzh_processed.png&w=3840&q=75)
Transcribed Image Text:You're essentially done. Please make sure you appreciate all the power you learned. You will put it
to good use soon.
NLP and Finding Characters
You will use the power of nltk to find characters in a novel. Write the function find_characters_nlp.
It will use n1tk.
[64] def find_characters_nlp(text, topn):
output = []
for sent in nltk.sent_tokenize(text):
tagged = nltk.pos_tag(nltk.word_tokenize (sent))
for chunk in nltk.ne_chunk(tagged):
if hasattr(chunk, 'label') and chunk.label() == "PERSON":
name = ' ¹.join(c[0] for c in chunk)
print (name)
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