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Introduction to Natural Language Processing (i-NLP) · Quiz 1 · Jan 2025

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Question 121 MCQ · 2.0 marks

Once the model is sufficiently trained, which of the following tokens will have the highest probability to be the next token, if the input is “Sachin has”:
  1. broken
  2. acted
  3. highest
  4. None of these       **i-NLP** **Section Id :** 64065379955 **Section Number :** 8 **Section type :** Online **Mandatory or Optional :** Mandatory **Number of Questions :** 31 **Number of Questions to be attempted :** 31 **Section Marks :** 50 **Display Number Panel :** Yes **Section Negative Marks :** 0 **Group All Questions :** No **Enable Mark as Answered Mark for Review and** No **Clear Response :** **Section Maximum Duration :** 0 **Section Minimum Duration :** 0 **Section Time In :** Minutes **Maximum Instruction Time :** 0

A published solution is not available for this question yet.

Question 123 MCQ · 2.0 marks

Consider the following conversation: User: “It’s quite cold in here.” Bot: “Yes, the temperature is 20\(^{o}\)C.” User: “Could you help?” Bot: “What would you like help with?” Which level of language processing is the chatbot failing to implement effectively?
  1. Lexical
  2. Discourse
  3. Pragmatic
  4. Syntactic

A published solution is not available for this question yet.

Question 124 MCQ · 2.0 marks

Statement: “Lexical ambiguity occurs when an individual word has multiple dictionary meanings.”
  1. Yes
  2. No

A published solution is not available for this question yet.

Question 125 MCQ · 2.0 marks

What makes the example “Time flies like an arrow” particularly challenging for POS tagging?
  1. The presence of words with ambiguous lexical categories that can lead to multiple syntactic structures.
  2. Difficulty in identifying compound nouns within the sentence.
  3. The sentence contains idiomatic expressions that require semantic understanding.
  4. The use of archaic word forms.

A published solution is not available for this question yet.

Question 126 MCQ · 2.0 marks

Anaphora resolution can be fully solved using only syntactic parsing techniques.
  1. Yes
  2. No

A published solution is not available for this question yet.

Question 127 MCQ · 2.0 marks

Which of the following statements correctly describes the relationship between Finite State Automata (FSA) and Finite State Transducers (FST)?
  1. FSAs are designed solely for recognizing patterns in input strings, while FSTs can recognize patterns and produce corresponding outputs.
  2. Both FSAs and FSTs utilize a single tape for processing input, but FSAs have a fixed number of states while FSTs can dynamically change the number of states during execution.
  3. FSTs can be used to perform computations involving multiple input tapes, whereas FSAs are limited to a single input tape.
  4. FSA can produce outputs based on their input states, while FSTs are only capable of recognizing inputs without generating outputs.

A published solution is not available for this question yet.

Question 128 MCQ · 2.0 marks

Which of the following sequences represents a valid order of calculations in the Forward algorithm of HMM?
  1. Calculate state probabilities → Update observation probabilities → Compute final sequence probability
  2. Initialize state probabilities → Calculate joint probabilities → Sum over all possible paths
  3. Calculate emission probabilities → Sum transition probabilities → Normalize final states
  4. Initialize α1(i) → Calculate αt(i) recursively → Sum over final states

A published solution is not available for this question yet.

Question 129 MCQ · 2.0 marks

Which feature combination would be most effectively handled by CRF but not by HMM for POS tagging?
  1. Current word and its immediate next word
  2. Word length and first character capitalization
  3. Previous tag and current word ending
  4. Current word’s morphological features combined with a window of ±2 words and their POS tags

A published solution is not available for this question yet.

Question 130 MCQ · 2.0 marks

[[IMAGE:3f7e5c5e1c350490_4_0]]
Source diagram or notation
  1. 1-B, 2-C, 3-A, 4-D
  2. 1-A, 2-B, 3-C, 4-D
  3. 1-B, 2-A, 3-D, 4-C
  4. 1-D, 2-C, 3-B, 4-A

A published solution is not available for this question yet.

Question 131 MCQ · 2.0 marks

[[IMAGE:3f7e5c5e1c350490_4_1]]
Source diagram or notation
  1. 1.5
  2. 1.6
  3. 1.7
  4. 1.8

A published solution is not available for this question yet.

Question 132 MCQ · 2.0 marks

In evaluating a dependency parser, the following results were obtained on a test set of 500 words: • 450 words have the correct head • 425 words have both the correct head and correct label • 475 words have the correct label What are the Unlabeled Attachment Score (UAS) and Label Accuracy Score (LS)?
  1. UAS: 90%, LS: 95%
  2. UAS: 90%, LS: 85%
  3. UAS: 85%, LS: 95%
  4. UAS: 85%, LS: 90%

A published solution is not available for this question yet.

Question 133 MCQ · 1.0 marks

The phonological level of NLP processing is crucial for improving the performance of text-based sentiment analysis systems.
  1. Yes
  2. No

A published solution is not available for this question yet.

Question 134 MCQ · 1.0 marks

In the sentence “I saw her duck,” morphological analysis alone is sufficient to determine whether “duck” is being used as a noun or a verb.
  1. Yes
  2. No

A published solution is not available for this question yet.

Question 135 MCQ · 1.0 marks

Which would be the most appropriate approach for processing millions of search queries in real- time?
  1. Lemmatization
  2. Stemming
  3. Full morphological analysis
  4. Manual word reduction

A published solution is not available for this question yet.

Question 136 MCQ · 1.0 marks

Which approach would be most appropriate for building a dictionary lookup system?
  1. Stemming
  2. Lemmatization
  3. Simple suffix removal
  4. No word reduction

A published solution is not available for this question yet.

Question 137 MCQ · 1.0 marks

Rule-based POS tagging always results in accurate tagging because it relies on linguistic rules rather than probabilities.
  1. Yes
  2. No

A published solution is not available for this question yet.

Question 138 MCQ · 1.0 marks

Which of the following demonstrates an “overlapping entity” scenario in NER?
  1. Albert Einstein and Theory of Relativity
  2. Amazon and Amazon River
  3. Tesla and Model S
  4. Shakespeare and Hamlet

A published solution is not available for this question yet.

Question 139 MCQ · 1.0 marks

Consider the following phrase structure rule: NP → (Det) (Adj)* N (PP)* Which of the following statements about this rule is FALSE?
  1. It allows for multiple consecutive adjectives before the noun.
  2. It requires exactly one determiner before any adjectives.
  3. It permits zero or more prepositional phrases after the noun.
  4. The noun is the only mandatory element in this noun phrase.

A published solution is not available for this question yet.

Question 140 MCQ · 1.0 marks

Given the sentence “The chef cooked a meal for the guests using fresh ingredients,” identify the Semantic Roles of the sentence.
  1. Agent: Chef, Theme: Meal, Beneficiary: Guests, Instrument: Ingredients
  2. Agent: Meal, Theme: Guests, Beneficiary: Chef, Instrument: Cooking
  3. Agent: Chef, Theme: Ingredients, Beneficiary: Meal, Instrument: Guests
  4. Agent: Ingredients, Theme: Chef, Beneficiary: Meal, Instrument: Cooking

A published solution is not available for this question yet.

Question 141 MCQ · 1.0 marks

Context-Free Grammar (CFG) rules can only generate sentences with a fixed word order.
  1. Yes
  2. No

A published solution is not available for this question yet.

Question 142 MCQ · 1.0 marks

The CKY parsing algorithm requires the grammar to be in Chomsky Normal Form (CNF).
  1. Yes
  2. No

A published solution is not available for this question yet.

Question 143 MCQ · 1.0 marks

In the sentence “He gave her a book,” the dependency relationship between “gave” and “book” is labeled as nsubj.
  1. Yes
  2. No

A published solution is not available for this question yet.

Question 144 MCQ · 1.0 marks

Which evaluation metric would you use to measure the proportion of correct dependency relations retrieved by a parser from the total number of correct relations?
  1. Precision
  2. Recall
  3. F1 Score
  4. Accuracy

A published solution is not available for this question yet.

Question 145 MCQ · 3.0 marks

[[IMAGE:3f7e5c5e1c350490_8_2]]
Source diagram or notation
  1. 0.0090
  2. 0.036
  3. 0.0045
  4. 0.0036

A published solution is not available for this question yet.

Question 146 MSQ · 1.0 marks

Which of the following are applications of clustering in NLP tasks? (Select all that apply)
  1. Grouping similar entities in NER
  2. Unsupervised POS tagging
  3. Sentiment analysis
  4. Word clustering into syntactic categories
  5. Machine translation

A published solution is not available for this question yet.

Question 147 MSQ · 2.0 marks

Which characteristics distinguish Morphological Analysis (MA)from POS tagging? (Select all that apply)
  1. MA is independent of syntactic rules, while POS tagging often depends on them
  2. MA may produce multiple analyses for a word while POS tagging produces one
  3. MA requires fewer categories compared to POS tagging
  4. MA assigns functional roles in a sentence, while POS tagging deals with form and structure.

A published solution is not available for this question yet.

Question 148 MSQ · 2.0 marks

What are potential issues when implementing stemming? (Select all that apply)
  1. Over-stemming
  2. Under-stemming
  3. Requiring a large dictionary
  4. Creating non-words

A published solution is not available for this question yet.

Question 149 MSQ · 2.0 marks

Which of the following are true about the relationship between POS tagging, NER, and classification models? (Select all that apply)
  1. Both POS tagging and NER can be framed as classification problems
  2. Naive Bayes and logistic regression can be applied to both tasks
  3. Clustering can be used as a preprocessing step for both tasks
  4. POS tagging always precedes NER in NLP pipelines
  5. Both tasks benefit from considering contextual information

A published solution is not available for this question yet.

Question 150 MSQ · 3.0 marks

Which of the following NLP tasks would benefit from processing at the discourse level? (Select all that apply)
  1. Generating a coherent multi-paragraph story
  2. Summarizing a long document
  3. Resolving pronouns in a conversation
  4. Determining the sentiment of a single word
  5. Identifying the topic shifts

A published solution is not available for this question yet.

Question 151 MSQ · 3.0 marks

Which of the following statements about stemming and lemmatization are true?
  1. **Stemming** can result in non-linguistic root forms, while **lemmatization** always produces valid words.
  2. **Lemmatization** requires a vocabulary or lexicon, whereas **stemming** does not.
  3. **Stemming** is computationally more expensive than **lemmatization** because it involves morphological analysis.
  4. Both **stemming** and **lemmatization** aim to reduce words to their root forms but differ in their approaches and accuracy.

A published solution is not available for this question yet.

Question 152 NAT · 2.0 marks

In a semantic role labeling evaluation, a model has identified 100 correct semantic roles out of 120 total semantic roles it predicted. What is the precision of the model as a decimal (rounded to two decimal places)?

    A published solution is not available for this question yet.