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Markov Assumption and Unigram Model

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Questions and Answers

What does the language model represent?

P(w1,w2…wn)

P(w1,w2…wn|wn)

P(wn|w1,w2…wn) (correct)

P(wn|w1)

What is the formula for the joint probability of multiple variables using the Chain Rule?

P(A,B,C,D) = P(A)P(B|A)P(C|A,B)P(D|A,B,C) (correct)

P(A,B,C,D) = P(A,B)P(C,D)

P(A,B,C,D) = P(A)P(B,C)P(D)

P(A,B,C,D) = P(A)P(B)P(C)P(D)

How is the probability of a sentence computed using the Chain Rule?

P(its, water, is, so, transparent) = P(its)P(water)P(is)P(so)P(transparent)

P(its, water, is, so, transparent) = P(its,water)P(is,so)P(transparent)

P(its, water, is, so, transparent) = P(its)P(water|its)P(is|its,water)P(so|its,water,is)P(transparent|its,water,is,so) (correct)

P(its, water,CommandEvent, so, transparent) = P(its)P(water,is)P(so,transparent)

Why can't we simply count and divide to estimate the probabilities of words in a sentence?

Because there are too many possible sentences Signup and view all the answers

What is the formula for estimating the probability of a word given the previous words using the Chain Rule?

P(w|w1,w2…wn-1) = P(w1,w2…wn-1,w) / P(w1,w2…wn-1) Signup and view all the answers

What is the purpose of the Chain Rule in language modeling?

To simplify the computation of joint probabilities Signup and view all the answers

How is the probability of a sentence P(W) computed in language modeling?

P(W) = P(w1)P(w2|w1)P(w3|w1,w2)…P(wn|w1,w2…wn-1) Signup and view all the answers

What is the advantage of using the Chain Rule in language modeling?

It enables the estimation of probabilities for unseen sentences Signup and view all the answers

What is the formula for the conditional probability p(B|A)?

p(B|A) = p(A,B) / p(A) Signup and view all the answers

What is the purpose of language modeling in NLP?

To estimate the probability of a sentence Signup and view all the answers