How to Fix – NameError name ‘wordnet’ is not defined

WordNet is a lexical data source for the English language, which is consisted of in the All-natural Language Toolkit (NLTK) corpus in Python. It offers a big collection of words and also their partnerships, such as basic synonyms, antonyms, hypernyms, hyponyms, and also meronyms. It is commonly made use of in all-natural language handling jobs such as message category, view evaluation, and also info access. The NLTK collection offers a wordnet corpus that you can utilize in your Python code. It can take place that when you’re attempting to utilize wordnet from the NLTK collection, you might encounter the “NameError: name ‘wordnet’ is not specified”.

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In this tutorial, we will certainly talk about exactly how to repair this mistake by importing the wordnet component properly. By the end of this tutorial, you will have a far better understanding of exactly how to import the wordnet component from the NLTK collection and also stay clear of usual mistakes.

Why does the NameError: name 'wordnet' is not defined happen?

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This mistake happens when you attempt to utilize the wordnet component from the NLTK collection in your Python code, yet Python can not locate the wordnet component in its namespace. This could take place if you are not properly importing the wordnet component.

Just how to properly import wordnet?

The right method to import the wordnet component is as adheres to–

1. Make certain that you have the nltk component set up. Usage pip program nltk inside command timely or incurable to examine if you have the nltk component set up or otherwise. If it is not set up, utilize pip set up nltk inside the command timely or incurable to set up the nltk component.

2. Import the nltk component.

3. Download and install the wordnet corpus making use of the nltk component making use of the command nltk. download(' wordnet') . This will certainly download and install the wordnet corpus to your computer system.

4. After downloading and install the wordnet corpus, you can import the wordnet component in your Python code making use of from nltk.corpus import wordnet

The over actions will certainly ensure that you have actually properly imported wordnet from the nltk component. Allow’s currently consider an instance of importing and also making use of the wordnet component from the nltk collection.

Thinking that the nltk component is set up.

 import nltk
# download and install the wordnet corpus
nltk.download(' wordnet').
# import wordnet.
from nltk.corpus import wordnet.
# obtain basic synonyms for words "pleased".
basic synonyms = [].
for syn in wordnet.synsets(" pleased"):.
for lemma in syn.lemmas():.
synonyms.append( lemma.name()).
# publish the listing of basic synonyms.
print( basic synonyms) 

Output:

[nltk_data] Downloading plan wordnet to/ Users/piyush/nltk _ information ...
['happy', 'felicitous', 'happy', 'glad', 'happy', 'happy', 'well-chosen']

In the above instance, we are publishing the basic synonyms for words “pleased” making use of the wordnet component from nltk. Keep in mind that WordNet teams words right into collections of basic synonyms called “synsets”, and also each synset consists of a checklist of lemmas (i.e., words with the exact same definition). In this instance, we loophole via all the synsets for words “pleased” and also include the lemma names to a checklist of basic synonyms.

We complied with the actions pointed out earlier and also hence really did not obtain a mistake.

Typical Mistakes when importing wordnet

Let’s currently consider some usual situations that can lead to mistakes while importing the wordnet component.

NameError: name 'wordnet' is not defined

A usual blunder individuals do is that they download and install the wordnet corpus yet fail to remember to import it. Like in the instance below–

import nltk.
# download and install the wordnet corpus.
nltk.download(' wordnet').
# obtain basic synonyms for words "pleased".
basic synonyms = [].
for syn in wordnet.synsets(" pleased"):.
for lemma in syn.lemmas():.
synonyms.append( lemma.name()).
# publish the listing of basic synonyms.
print( basic synonyms) 

Output:

[nltk_data] Downloading plan wordnet to/ Users/piyush/nltk _ information ...
---------------------------------------------------------------------------.
NameError Traceback (latest phone call last).
Cell In[1], line 8.
6 # obtain basic synonyms for words "pleased".
7 basic synonyms = [].
-- > 8 for syn in wordnet.synsets(" pleased"):.
9 for lemma in syn.lemmas():.
10 synonyms.append( lemma.name()).
NameError: name 'wordnet' is not defined

Using nltk. download(' wordnet') will certainly download and install the wordnet corpus to your computer system yet in order to utilize it in your Python code, you still need to import the wordnet component. You can import the wordnet component making use of from nltk.corpus import wordnet.

LookupError: source 'wordnet' was not found

If the wordnet corpus is not downloaded and install on your equipment and also you attempt to import the wordnet, it will certainly provide you a LookupError.

 import nltk.
# import wordnet.
from nltk.corpus import wordnet.
# obtain basic synonyms for words "pleased".
basic synonyms = [].
for syn in wordnet.synsets(" pleased"):.
for lemma in syn.lemmas():.
synonyms.append( lemma.name()).
# publish the listing of basic synonyms.
print( basic synonyms) 

Output:

 ---------------------------------------------------------------------------.
LookupError:.
**********************************************************************.
Source wordnet not located.
Please utilize the NLTK Downloader to acquire the source:.
>>> > > > import nltk.
>>> > > > nltk.download(' wordnet').
********************************************************************** 

To prevent this mistake, ensure that the wordnet corpus is downloaded and install prior to you import it right into your code.

Conclusion

In verdict, the “NameError name ‘wordnet’ is not specified” mistake can be irritating when dealing with all-natural language handling jobs. Nonetheless, by adhering to the actions detailed in this tutorial, you can quickly repair this mistake and also proceed with your NLP job. Bear in mind to import the needed collections and also components, and also guarantee that you have actually set up the needed plans. With these easy repairs, you can conquer this mistake and also effectively full your NLP jobs.

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