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NLP_W9_B1

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

What is the thematic role of the entity that performs the action in a sentence?

a)

Patient

b)

Beneficiary

c)

Theme

d)

Agent

2.

In the sentence, "The teacher gave the book to the student," what is the thematic role of "the student"

a)

Agent

b)

Goal

c)

Beneficiary

d)

Theme

3.

Which of the following sentences has a clear example of a "Location" thematic role

a)

John put the book on the shelf.

b)

He cut the paper with scissors.

c)

She made a cake for her mother.

d)

The book was given to the student.

4.

What is the primary goal of PropBank annotation

a)

To identify coreference chains

b)

To assign semantic roles to arguments of verbs

c)

To determine word frequency

d)

To analyze sentence syntax

5.

Which of the following is TRUE about PropBank annotation

a)

It labels arguments of verbs with semantic roles.

b)

It involves annotating the syntactic structure of sentences.

c)

It focuses on part-of-speech tagging.

d)

It is based on dependency structures.

6.

Which component of a sentence is typically labeled as "Arg2" in PropBank

a)

Direction or endpoint of the action

b)

Instrument

c)

Manner

d)

Beneficiary

7.

In a Markov Chain, the probabilities associated with moving from one state to another are known as:

a)


Steady-state probabilities

b)

Initial state probabilities

c)

Transition probabilities

d)

Absorbing probabilities

8.

What is a "steady-state" distribution in a Markov Chain

a)

The distribution of states for an absorbing Markov Chain

b)

The distribution of states with zero transitions

c)

The distribution of states after a large number of steps, where probabilities no longer change

d)

The distribution of states at the first time step

9.

In a Markov Chain, if the system has a finite number of states and the transition matrix is stochastic, then:

a)

The system will eventually reach an absorbing state

b)

The system can never reach a steady state

c)

The row sums of the transition matrix must equal 1

d)

The system has an infinite number of possible states

10.

Which of the following is an example of a Markov process

a)

A system with random transitions based on previous states and external factors

b)

A coin flip where the outcome depends on previous flips

c)

A weather model where tomorrow’s weather depends only on today’s weather

d)

Stock prices where tomorrow’s price depends on the entire past history