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. **Understanding a Simple Markov Model in Linguistics**A special human language is composed exclusively of nouns and verbs. A sentence begins with a noun with a 75% probability and with a verb at 25%. If a given word is a noun, there is a 75% likelihood the next word will be a verb, and a 25% chance it will be a noun. If a given word is a verb, there's a 75% chance the next word will be a noun and a 25% chance it will be a verb. This language can be modeled using a Markov chain with two states: noun and verb.**1. Markov Chain Practice:**When drawing the Markov chain for this language, it should feature:- Only two nodes and four directed edges.- Each nodal transition, such as from "noun" to "verb", will have a weight of 0.75, while "verb" to "noun" also carries a weight of 0.75.**2. Probability of Initial Sentence Structure:**Calculate the probability that the first three words of a sentence are all nouns:- Approximately 4.69%.**3. Determining the Third Word's Part of Speech:**Identify the probability that the third word in a sentence is a noun:- 25% chance.**4. Analyzing "Yacc grep":**For the sentence "Yacc grep," determine the most probable part-of-speech sequence using brute-force evaluation of all potential sequences. Choose the sequence with the highest probability:- Noun 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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