A certain little-known human language consists of only nouns and verbs. A sentence begins with a noun with probability 75% and with a verb with probability 25%. If a given word in a sentence is a noun, there is a 75% probability that the next word is a verb and a 25% probability that the next word is a noun. If a given word is a verb, there is a 75% probability that the next word in the sentence is a noun, and a 25% probability that is a verb.We can model this language using a Markov chain with two states: noun and verb. A certain little-known human language consists of only nouns and verbs. A sentence begins witha noun with probability 75% and with a verb with probability 25%. If a given word in a sentence isa noun, there is a 75% probability that the next word is a verb and a 25% probability that the nextword is a noun. If a given word is a verb, there is a 75% probability that the next word in thesentence is a noun, and a 25% probability that is a verb.We can model this language using a Markov chain with two states: noun and verb.To get some practice, draw the Markov chain that models this language on apiece of paper. The Markov chain has... (mark all that apply)O exactly 2 nodes and 4 directed edgesexactly 2 nodes and 4 undirected edgesO exactly 2 nodes and 2 directed edgesO an edge from "noun" to "verb" that has a weight of 0.75O an edge from "verb" to "noun" that has a weight of 0.252What is the probability that the first three words of a sentence are all nouns?O around 1.56%O around 4.69%O around 14.06%O around 42.19%What is the probability that the third word of a sentence is a noun?O 21.875%© 25%O 56.25%O 37.5%4 Finally, consider observing the sentence "Yacc grep." What is the most likelypart-of-speech state sequence (i.e. sequence of nouns and verbs) that couldhave resulted in this sentence?As an exercise for now, just use a brute-force search over all 4 possiblesequences, i.e. compute all 4 and choose the one with the highest probability.In the next lecture, we will see how to do this more efficiently using theViterbi algorithm.O Noun NounO Noun VerbO Verb NounO Verb Verb

As per the bartleby policy I answered the first three subparts

A certain little-known human language consists of only nouns and verbs. A sentence begins with a noun with probability 75% and with a verb with probability 25%. If a given word in a sentence is a noun, there is a 75% probability that the next word is a verb and a 25% probability that the next word is a noun. If a given word is a verb, there is a 75% probability that the next word in the sentence is a noun, and a 25% probability that is a verb. We can model this language using a Markov chain with two states: noun and verb.

A certain little-known human language consists of only nouns and verbs. A sentence begins with a noun with probability 75% and with a verb with probability 25%. If a given word in a sentence is a noun, there is a 75% probability that the next word is a verb and a 25% probability that the next word is a noun. If a given word is a verb, there is a 75% probability that the next word in the sentence is a noun, and a 25% probability that is a verb. We can model this language using a Markov chain with two states: noun and verb.

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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