Which of the following is an example of a language model that uses a probabilistic approach?

NLP_B2_W7

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Engineering
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University
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Medium
Prashanthi Prashanthi
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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Rule-based model
Hidden Markov model (HMM)
Decision tree
Convolutional neural network (CNN)
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is a limitation of HMMs?
They may not capture long-range dependencies well
They require minimal training data
They are easy to implement
They can model sequences of data
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What assumption does an HMM make regarding the Markov property?
Observations are independent
There are no hidden states
The next state depends only on the current state
The next state depends on all previous states
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In an HMM, what do the "hidden states" represent?
The final output of the model
The input data
The underlying processes that generate observations
The visible outcomes in a sequence
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following techniques can improve the accuracy of POS tagging?
Reducing the dataset size
Ignoring punctuation
Using context and surrounding words
Increasing the number of stop words
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What challenge does POS tagging face with the word "lead" in the sentence "He will lead the team"?
Long sentences
None of the above
Lack of training data
Ambiguity due to multiple meanings
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary purpose of POS tagging in NLP?
To assign grammatical categories to words in a sentence
To summarize the main ideas of a document
To identify the sentiment of a text
To translate text into different languages
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