Natural Language Processing (NLP) MCQs (Multiple-Choice Questions)

1. What is NLP?

1. A subfield of Computer science to understand and process natural language using AI
2. A search engine
3. An image editor
4. None of the above

Answer: A) A subfield of Computer science to understand and process natural language using AI

Explanation:

NLP, Natural Language Processing, is a subfield of Computer Science to understand and process natural language with the help of Artificial Intelligence, AI.

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2. What is Ambiguity in the context of NLP?

1. Ability of being understood in multiple ways
2. Inability to understand a word
3. Both of the above
4. None of the above

Answer: A) Ability of being understood in multiple ways

Explanation:

Natural Language is ambiguous by nature. Many words/ sentences can have different meanings in different contexts. In the case of NLP, this possibility of being understood is known as Ambiguity.

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3. What is Lexical Ambiguity in the context of NLP?

1. Ambiguity of a sentence
2. Ambiguity of single word
3. Ambiguity of phrase of a sentence
4. None of the above

Answer: B) Ambiguity of single word

Explanation:

Lexical Ambiguity refers to the ambiguity due to a single word. For example, a word Silver can be treated as a noun, adjective or as a verb.

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4. What is Syntactic Ambiguity in the context of NLP?

1. Ambiguity of a sentence
2. Ambiguity of single word
3. Ambiguity of phrase of a sentence
4. None of the above

Answer: A) Ambiguity of a sentence

Explanation:

When a sentence can be parsed in multiple ways, the ambiguity caused is termed as Syntactic Ambiguity. Consider the case in the following sentence, 'Man saw a boy with a magnifying glass'. Here the sentence is ambiguous as to whether the man saw a boy carrying a magnifying glass or man saw the boy with the help of a magnifying glass.

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5. What is Semantic Ambiguity in the context of NLP?

1. Ambiguity of a sentence
2. Ambiguity of single word
3. Ambiguity of phrase of a sentence
4. None of the above

Answer: C) Ambiguity of phrase of a sentence

Explanation:

When a sentence contains ambiguous words/phrases, the ambiguity caused is termed as Syntactic Ambiguity. Consider the case in the following sentence, 'A truck hit the pole when it was moving'. Here the sentence is ambiguous as to whether the truck, while moving hit the pole or truck hit the moving pole.

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6. What is Anaphoric Ambiguity in the context of NLP?

1. Ambiguity of a sentence
2. Ambiguity of single word
3. Ambiguity of phrase of a sentence
4. None of the above

Answer: D) None of the above

Explanation:

Anaphoric ambiguity arises when anaphoric entities are used. Consider the following sentences. A goat rode up the hill. It was very steep. It reached quickly though. Here use of It causes anaphoric ambiguity.

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7. What is Pragmatic Ambiguity in the context of NLP?

1. Ambiguity of a context of phrase
2. Ambiguity of single word
3. Ambiguity of a sentence
4. None of the above

Answer: A) Ambiguity of a context of phrase

Explanation:

Pragmatic ambiguity arises when the context of a sentence or phrase can be interpreted in many ways. Consider a case of 'I like you too' can be interpreted as 'I like you' as you like me or 'I like you' as anyone does.

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8. Which of the following is true about Morphological Processing in the context of NLP?

1. It is the first phase of NLP
2. It breaks the chunks of language into tokens
3. Both of the above
4. None of the above

Answer: C) Both of the above

Explanation:

Morphological Processing is the first phase of NLP. Main purpose of Morphological processing is to break the chunks of the language to tokens corresponding to words, sentences or paragraphs. For example, 'uneasy' can be divided into a subword token as 'un-easy'.

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9. Which of the following is true about Syntax Analysis in the context of NLP?

1. It is the second phase of NLP
2. It checks if the sentence is well formed
3. It creates a structure showing the syntactical relationship between words
4. All of the above

Answer: D) All of the above

Explanation:

Syntax Analysis is the second phase of NLP. Main purpose of the Syntax Analysis phase is twofold. First to check if the sentence is well formed and secondly to create a structure showing the syntactical relationship between words. For example, an invalid sentence like 'The school is going to the boy.' will be rejected by the Syntax Analysis phase.

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10. Which of the following is true about Semantic Analysis in the context of NLP?

1. It is the third phase of NLP
2. It checks the meaningfulness of a sentence
3. Both of the above
4. None of the above

Answer: C) Both of the above

Explanation:

Semantic Analysis is the third phase of NLP. Main purpose of the Semantic Analysis phase is to check the meaningfulness of a sentence like the dictionary meaning. For example, semantic analysis will reject a sentence like 'Hot icecream.'

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11. Which of the following is true about Pragmatic Analysis in the context of NLP?

1. It is the fourth phase of NLP
2. It fits the objects/events with references.obtained in semantic analysis
3. Both of the above
4. None of the above

Answer: C) Both of the above

Explanation:

Pragmatic Analysis is the fourth and last phase of NLP. Main purpose of the Pragmatic Analysis phase is to set the objects/events obtained in the previous step, semantic analysis, at their right place. For example, 'Put the ball in the basket on a shelf' may have two semantic interpretations. Pragmatic analysis will choose one of the possibilities.

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12. What is Corpus in terms of NLP?

1. A large structured set of machine-readable text
2. Dictionary of words
3. Both of the above
4. None of the above

Answer: A) A large structured set of machine-readable text

Explanation:

Corpus is a large structured set of machine-readable text produced during communications. A corpus can be derived from multiple sources like data available in electronic form, transcripts or even using OCR, Optical Character Recognition etc.

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13. Which of the following is an element of Corpus Design?

1. Corpus Balance
2. Sampling
3. Corpus Size
4. All of the above

Answer: D) All of the above

Explanation:

Corpus Balance, Sampling and Corpus Size all are integral parts of a Corpus Design. Corpus balance refers to the wide range of the text categories as representatives of the language. Sampling is used to get a subset of data which can be used to represent the large set of information and Corpus Size represents the size of the Corpus.

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14. Which of the following is a valid type of Corpus?

1. TreeBank Corpus
2. PropBank Corpus
3. Both of the above
4. None of the above

Answer: C) Both of the above

Explanation:

TreeBank and PropBank, both are types of Corpus. TreeBank Corpus is a linguistic parsed text-based corpus which annotates syntactic or semantic sentence structure whereas PropBank Corpus or more specifically Proposition Bank Corpus is a corpus which is annotated with verbal propositions and their arguments.

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15. Which of the following are valid types of TreeBank Corpus?

1. Semantic TreeBanks
2. Syntactic TreeBanks
3. Both of the above
4. None of the above

Answer: C) Both of the above

Explanation:

Semantic TreeBanks and Syntactic TreeBanks are the most common types of TreeBanks.Semantic TreeBank uses formal representation of semantic structure of sentences. Syntactic TreeBank uses expressions of formal language retrieved from parsed treebank data.

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16. Which of the following is a Semantic TreeBank Corpus?

1. Robot Commands TreeBanks
2. Geoquery
3. Groningen Meaning Bank
4. All of the above

Answer: C) Groningen Meaning Bank

Explanation:

Robot Commands Treebank, Geoquery, Groningen Meaning Bank, RoboCup Corpus are popular Semantic Treebanks.

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17. Which of the following is a Syntactic TreeBank Corpus?

1. Penn Arabic TreeBank
2. Columbia Arabic TreeBank
3. Sinina
4. All of the above

Answer: D) All of the above

Explanation:

Penn Arabic Treebank, Columbia Arabic Treebank are syntactic Treebanks in Arabia language. Sininca is a syntactic Treebank in Chinese language. Lucy, Susane and BLLIP WSJ syntactic treebank corpus in English language.

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18. What is Morphological Parsing in terms of NLP?

1. Parsing of morphemes
2. Breaking down words into smaller meaning units called morphemes
3. Both of the above
4. None of the above

Answer: C) Both of the above

Explanation:

Morphological parsing refers to parsing of morphemes. A morpheme represents the smallest meaningful units. For example, consider a word, boxes, we can break it into two words/morphemes box and es.

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19. Morphology is a study of?

1. Formation of words
2. Origin of words
3. Grammatical formation of words
4. All of the above

Answer: D) All of the above

Explanation:

Morphology is study of following:

• Words formation.
• Words origin.
• Grammatical formations of the words.
• Usage of prefixes and suffixes in word formation.
• Formation of parts-of-speech (PoS) of a language.

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20. Which of the following is a valid type of Morpheme?

1. Stem
2. Word Order
3. Both of the above
4. None of the above

Answer: C) Both of the above

Explanation:

Morphemes are the smallest meaningful units and can be divided into following types:

• Stems
• Word Order

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21. Which of the following correctly defines the role of a parser?

1. A Parser reports any syntax error
2. A Parser recovers from a common error to continue processing of the rest of the program
3. A Parser creates a parse tree
4. All of the above

Answer: D) All of the above

Explanation:

A Parser is a software component which takes text as input and gives structural representation of input after checking it against the grammar of the language. Main roles of a parser are following:

• To report any syntax error.
• To recover from commonly occurring errors to continue parsing of the rest of the program.
• To create a parse tree
• To create a symbol tree
• To produce intermediate representations.

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22. Which of the following correctly defines Top-Down parser?

1. Top-Down Parser starts parsing the tree from the start symbol, constructing the tree up to the input symbol
2. Top-Down Parser starts parsing from the input symbol and constructs the tree up to the start symbol
3. Both of the above
4. None of the above

Answer: A) Top-Down Parser starts parsing the tree from the start symbol, constructing the tree up to the input symbol

Explanation:

Top-Down Parser starts parsing the tree from the start symbol, constructing the tree up to the input symbol. Top-Down parser uses a recursive procedure to process the inputs.

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23. Which of the following correctly defines Bottom-Up parser?

1. Bottom-Down Parser starts parsing the tree from the start symbol, constructing the tree up to the input symbol
2. Bottom-Down Parser starts parsing from the input symbol and constructs the tree up to the start symbol
3. Both of the above
4. None of the above

Answer: B) Bottom-Down Parser starts parsing from the input symbol and constructs the tree up to the start symbol

Explanation:

Bottom-Down Parser starts parsing the input symbol and constructs the tree up to the start symbol.

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24. Which of the following correctly defines left-most derivation?

1. Sentential form of an input is scanned and replaced from left to right
2. Sentential form of an input is scanned and replaced from right to the left
3. Both of the above
4. None of the above

Answer: A) Sentential form of an input is scanned and replaced from left to right

Explanation:

Sentential form or more specifically left sentential form of an input is scanned and replaced from left to the right in left-most derivation

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25. Which of the following correctly defines right-most derivation?

1. Sentential form of an input is scanned and replaced from left to right
2. Sentential form of an input is scanned and replaced from right to the left
3. Both of the above
4. None of the above

Answer: B) Sentential form of an input is scanned and replaced from right to the left

Explanation:

Sentential form or more specifically right sentential form of an input is scanned and replaced from right to the left in right-most derivation.

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26. Which of the following is correct about Parse Tree?

1. It is a graphical representation of a derivation
2. Root of the parse tree is denoted by the start symbol of derivation
3. Terminals are denoted by leaf nodes and non-terminals are denoted by internal nodes
4. All of the above

Answer: D) All of the above

Explanation:

A parse tree can be defined as a graphical representation of a derivation. Root of the parse tree denotes the start symbol of derivation. Leaf nodes denote the terminals and internal nodes denote the non-terminals.

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