NLP Quiz Questions PDF

1) What is the study of morphology in NLP? a) Study of sentence structure b) Study of word structure c) Study of semantic meaning d) Study of syntax 2) What is a morpheme? a) The smallest grammatical unit of meaning b) A sentence structure c) A type of syntactic c...

1) What is the study of morphology in NLP? a) Study of sentence structure b) Study of word structure c) Study of semantic meaning d) Study of syntax 2) What is a morpheme? a) The smallest grammatical unit of meaning b) A sentence structure c) A type of syntactic category d) A word pair 3) Which of these is a derivational morpheme? a) -ing b) un- c) -s d) -ed 4) Which of these is a free morpheme? a) -ly b) -ed c) dog d) -s 5) What is stemming used for? a) To group inflected forms of words b) To map words to their grammatical structure c) To create new morphemes d) To identify POS tags 6) Which NLP task often relies on morphological parsing? a) Part-of-speech tagging b) Word sense disambiguation c) Text summarization d) Semantic analysis 7) What does a parse tree represent? a) The grammatical structure of a sentence b) Word-to-word semantic relations c) Surface forms of words d) Probabilities of sentence formation 8) Which of the following is an example of inflectional morphology? a) Adding the suffix -ed to a verb b) Adding the prefix un- to an adjective c) Combining two words into a compound d) Creating a new lexeme through derivation 9) What is the main purpose of tokenization in NLP? a) Splitting text into meaningful units b) Identifying grammatical structure c) Assigning word senses d) Resolving ambiguity 10) What is a context-free grammar (CFG)? a) A set of rules generating syntactically valid sentences b) A probabilistic model for parsing c) A semantic analysis tool d) A rule-based lexicon generator 11) What is syntactic ambiguity? a) A sentence having multiple grammatical interpretations b) A word having multiple meanings c) Incorrect tagging of words d) Failure to parse sentences 12) What is a probabilistic context-free grammar (PCFG)? a) A rule-based syntactic model b) A method for semantic disambiguation c) A tool for morphological analysis d) A CFG with probabilities assigned to production rule 13) "I saw bats" contains which type of ambiguity? a) Syntactic b) Semantic c) Lexical d) Anaphoric 14) The words "bank/data bank/blood bank" is an example of ----------- a) Homophony b) Synonymy c) Polysemy d) Hyponymy 15) HMM are designed to model the joint distribution P(H , O) , where H is the _____state and O is the ________ state a) Hidden, Observed b) Unobservable, Hidden c) Classified, Completed d) Open, Completed 16) Elements of Semantic analysis a) Hyponymy b) Homonymy c) Polysemy d) Hyponymy, Homonymy, Polysemy 17) Which of the following is a example of irregular noun form? a) Fox b) Dog c) Mouse d) Cat 18) What is the role of syntactic analysis in NLP? a) Understanding sentence structure b) Assigning semantic meanings c) Resolving word ambiguities d) Tokenizing text 19).______ morphology is a type of word formation that creates new lexemes a) Derivational morphology b) Compound morphology c) Inflectional morphology d) Complex morphology 20) Which approach to WSD uses dictionaries or thesauri? a) Dictionary-based approach b) Corpus-based approach c) Rule-based approach d) Statistical approach 21) What is syntactic structure used for in NLP? a) To determine grammatical relationships in a sentence b) To resolve semantic ambiguity c) To identify word meanings d) To tokenize text 22) What is the primary challenge of syntactic analysis? a) Resolving syntactic ambiguity b) Assigning part-of-speech tags c) Identifying morphemes d) Resolving semantic ambiguity 23) Which NLP task is primarily concerned with analyzing sentence structure? a) Syntactic analysis b) Semantic analysis c) Morphological parsing d) Named entity recognition 24) What is syntactic analysis? a) Resolving word sense ambiguity b) Analyzing morphemes c) Generating semantic graphs d) Parsing the grammatical structure of sentences 25) Which type of representation is used in syntactic analysis? a) Parse tree b) Semantic graph c) Morpheme tree d) Word embeddings 26) What does a parse tree represent? a) The grammatical structure of a sentence b) Word-to-word semantic relations c) Surface forms of words d) Probabilities of sentence formation 27) Which term describes words that have the same spelling but different meanings? a) Homonyms b) Synonyms c) Antonyms d) Hyponyms 28) What is a context-free grammar (CFG)? a) A set of rules generating syntactically valid sentences b) A probabilistic model for parsing c) A semantic analysis tool d) A rule-based lexicon generator 29) What is the goal of semantic parsing? a) Extracting structured meaning from text b) Identifying sentence boundaries c) Generating parse trees for grammar d) Resolving lexical ambiguity 30) Which algorithm is used for parsing sentences in CFG? a) CYK algorithm b) Baum-Welch algorithm c) Viterbi algorithm d) Brill’s Tagger 31) What does statistical parsing rely on? a) Probabilistic context-free grammars b) Deterministic rules c) Morpheme analysis d) Semantic embeddings 32) What is syntactic ambiguity? a) A sentence having multiple grammatical interpretations b) A word having multiple meanings c) Incorrect tagging of words d) Failure to parse sentences 33) Which parsing technique uses probabilities to select the most likely parse tree? a) Statistical parsing b) Rule-based parsing c) Morphological parsing d) Neural parsing 34) Which component of HMM represents transitions between states? a) Transition probabilities b) Emission probabilities c) Initial state probabilities d) Observation matrix 35) What is a probabilistic context-free grammar (PCFG)? a) A CFG with probabilities assigned to production rules b) A rule-based syntactic model c) A method for semantic disambiguation d) A tool for morphological analysis 36) What type of grammar is used in syntactic analysis? a) Context-free grammar b) Lexical grammar c) Semantic grammar d) Morphological grammar 37) What is a top-down parsing algorithm? a) Begins parsing from the root of the parse tree b) Starts parsing from the leaves of the parse tree c) Uses morphological rules for parsing d) Generates semantic graphs 38) What are the two components of FST? a) Transition and output probabilities b) Input states and output symbols c) Rules and transformations d) Tags and syntactic structures 39) What is the role of syntactic analysis in NLP? a) Understanding sentence structure b) Assigning semantic meanings c) Resolving word ambiguities d) Tokenizing text 40) What is bottom-up parsing? a) Starts with the input symbols and builds up the parse tree b) Starts with the root node of the parse tree c) Resolves semantic ambiguities first d) Generates morphological forms 41) What is the difference between statistical parsing and rule-based parsing? a) Statistical parsing uses probabilities, while rule-based parsing uses fixed rules b) Rule-based parsing is faster than statistical parsing c) Statistical parsing uses semantic information, while rule-based parsing uses syntax d) There is no difference 42) What is syntactic structure used for in NLP? a) To determine grammatical relationships in a sentence b) To resolve semantic ambiguity c) To identify word meanings d) To tokenize text 43) What is a dependency tree? a) A tree showing grammatical relationships between words in a sentence b) A tree showing morphological forms c) A probabilistic graph of semantic roles d) A hierarchical structure of word senses 44) What is head-dependent structure in syntactic analysis? a) A grammatical relationship where one word governs another b) A morphological relationship between affixes c) A probabilistic relationship in PCFGs d) A semantic relationship between lexemes 45) What is the difference between lemmatization and stemming? a) Stemming is more accurate than lemmatization b) Lemmatization provides root words, while stemming cuts endings c) Lemmatization creates new words d) Stemming focuses on semantic analysis 46) What is the primary challenge of syntactic analysis? a) Resolving syntactic ambiguity b) Assigning part-of-speech tags c) Identifying morphemes d) Resolving semantic ambiguity 47) What is a collocation in NLP? a) Words that frequently co-occur together b) Words that have multiple meanings c) Grammatical rules for sentence formation d) A statistical parsing method 48) What is dependency parsing used for? a) Identifying grammatical relationships between words b) Resolving word sense ambiguity c) Tokenizing text into sentences d) Extracting semantic roles 49) What is lexical semantics? a) Parsing of morphological components b) Analysis of syntactic structures c) Study of word meanings and relationships d) Generation of parse trees 50) What is Word Sense Disambiguation (WSD)? a) Assigning part-of-speech tags to words b) Determining the correct meaning of a word in context c) Resolving syntactic ambiguity d) Identifying sentence structures 51) Which approach to WSD uses dictionaries or thesauri? a) Rule-based approach b) Corpus-based approach c) Dictionary-based approach d) Statistical approach 52) Which of the following is NOT a feature of lexical semantics? a) Synonymy b) Hypernymy c) Syntactic ambiguity d) Polysemy 53) What is the output of lemmatization? a) Base form of a word b) Root morpheme c) Part-of-speech tag d) Syntactic category 54) What is Latent Semantic Analysis (LSA)? a) A method for extracting hidden relationships between words b) A syntactic parsing algorithm c) A probabilistic model for grammar d) A semantic dictionary 55) What does semantic analysis in NLP focus on? a) Meaning of words, phrases, and sentences b) Grammar of sentences c) Structure of morphemes d) Probabilistic parsing 56) Which of these represents relations among lexemes? a) Synonyms and antonyms b) Inflectional rules c) Syntax trees d) Hidden Markov Models 57) What is semantic role labeling? a) Identifying the role of words in a sentence b) Parsing sentences into morphemes c) Resolving ambiguity in word senses d) Generating dependency trees 58) What is hypernymy? a) A hierarchical relationship where one term is more general than another b) A relationship of synonyms c) A type of morphological analysis d) A type of syntactic rule 59) What is polysemy? a) A word having multiple meanings b) Two words having the same meaning c) Words that sound alike but differ in meaning d) Resolving sentence ambiguity 60) What is synonymy? a) Words with similar meanings b) Words with opposite meanings c) Words with hierarchical relationships d) Words with multiple meanings 61) Which semantic relation is the opposite of synonymy? a) Antonymy b) Hypernymy c) Hyponymy d) Polysemy 62) What is the primary purpose of WSD? a) To resolve ambiguity in word meanings b) To assign part-of-speech tags c) To parse sentences syntactically d) To perform morphological analysis 63) Which approach does LSA primarily rely on? a) Statistical patterns in large corpora b) Handcrafted rules c) Semantic dictionaries d) Part-of-speech tagging 64) Which type of ambiguity arises from multiple meanings of a word? a) Lexical ambiguity b) Syntactic ambiguity c) Semantic ambiguity d) Morphological ambiguity 65) What is the difference between stemming and lemmatization? a) Stemming trims words, while lemmatization gives base forms b) Lemmatization uses statistical models, while stemming uses rules c) Stemming is more accurate than lemmatization d) Lemmatization resolves ambiguity, while stemming tokenizes text 66) Which method is commonly used for rule-based part-of-speech tagging? a) Brill’s tagger b) CYK algorithm c) Baum-Welch algorithm d) Hidden Markov Model 67) What does hyponymy represent? a) A hierarchical relationship where one term is more specific than another b) A synonymic relationship c) A relationship of antonyms d) A probabilistic parsing rule 68) What is semantic ambiguity? a) A word or sentence having multiple possible meanings b) Unclear syntactic structures c) Ambiguous grammatical roles d) Difficulty in tokenizing text 69) Which model is commonly used for semantic representation? a) Word embeddings b) Finite state transducers c) Context-free grammars d) CYK algorithm 70) What is the key focus of lexical semantics? a) Morphological parsing b) Sentence grammar c) Parsing algorithms d) Word meanings and relationships 71) Which of these is NOT a semantic relation? a) Hypernymy b) Synonymy c) Morpheme segmentation d) Antonymy 72) What is the purpose of semantic role labeling in NLP? a) Identifying the grammatical roles of words b) Parsing morphological forms of words c) Resolving syntactic ambiguity d) Building parse trees for sentences 73) Which of the following best describes WordNet? a) A lexical database for the English language b) A semantic parsing tool c) A rule-based morphological analyzer d) A probabilistic context-free grammar 74) What is a homonym? a) Words that sound alike but have different meanings b) Words with similar meanings c) Words with opposite meanings d) Words that are syntactically ambiguous 75) What is semantic similarity? a) A measure of how similar two words or sentences are in meaning b) A parsing algorithm for syntax trees c) A type of morphological relationship d) A rule-based tagging system 76) What is part-of-speech tagging? a) Generating morphological rules b) Parsing sentence structures c) Resolving word sense ambiguity d) Assigning grammatical categories to words 77) What is the study of morphology in NLP? a) Study of sentence structure b) Study of word structure c) Study of semantic meaning d) Study of syntax 78) What does HMM stand for in POS tagging? a) Hierarchical Morphology Mapping b) Hidden Markov Model c) Head Morphological Model d) Hidden Morphological Mapping 79) What is the purpose of lemmatization? a) Convert words to their base forms b) Assign POS tags to words c) Resolve syntactic ambiguity d) Parse sentence structures 80) What type of morpheme cannot stand alone? a) Free morpheme b) Bound morpheme c) Inflectional morpheme d) Root morpheme 81) What are the two components of FST? a) Transition and output probabilities b) Input states and output symbols c) Rules and transformations d) Tags and syntactic structures 82) Which of these is a free morpheme? a) -ly b) -ed c) dog d) -s 83) What is the primary challenge in POS tagging? a) Ambiguity in word roles b) Parsing sentence structures c) Resolving syntactic rules d) Tokenizing text 84) What is the role of emission probabilities in HMM? a) Probability of a word given a tag b) Transition between tags c) Resolving ambiguity in morphemes d) Parsing syntax 85) \What does a parse tree represent? a) The grammatical structure of a sentence b) Word-to-word semantic relations c) Surface forms of words d) Probabilities of sentence formation 86) What is syntactic ambiguity? a) A sentence having multiple grammatical interpretations b) A word having multiple meanings c) Incorrect tagging of words d) Failure to parse sentences 87) What is the role of syntactic analysis in NLP? a) Understanding sentence structure b) Assigning semantic meanings c) Resolving word ambiguities d) Tokenizing text 88) What is bottom-up parsing? a) Starts with the input symbols and builds up the parse tree b) Starts with the root node of the parse tree c) Resolves semantic ambiguities first d) Generates morphological forms 89) What is lexical semantics? a) Study of word meanings and relationships b) Analysis of syntactic structures c) Parsing of morphological components d) Generation of parse trees 90) What is the main limitation of rule-based POS tagging? a) Inability to handle unknown words effectively b) High computational cost c) Ambiguity in sentence semantics d) Dependence on morphological rules 91) Which approach to WSD uses dictionaries or thesauri? a) Dictionary-based approach b) Corpus-based approach c) Rule-based approach d) Statistical approach 92) What is semantic role labeling? a) Identifying the role of words in a sentence b) Parsing sentences into morphemes c) Resolving ambiguity in word senses d) Generating dependency trees 93) Which approach does LSA primarily rely on? a) Statistical patterns in large corpora b) Handcrafted rules c) Semantic dictionaries d) Part-of-speech tagging 94) What is a corpus in POS tagging? a) A large annotated collection of text used for training b) A collection of semantic relations c) A set of morphological rules d) A lexicon of syntactic patterns 95) What is semantic similarity? a) A rule-based tagging system b) A parsing algorithm for syntax trees c) A type of morphological relationship d) A measure of how similar two words or sentences are in meaning 96) What is the purpose of a feature extraction step in NLP? a) Converting text data into numerical representations b) Resolving ambiguity in word senses c) Identifying grammatical rules d) Tokenizing text into sentences 97) Which type of morpheme conveys grammatical information? a) Inflectional morpheme b) Derivational morpheme c) Free morpheme d) Bound morpheme 98) What is the challenge in machine translation systems? a) Resolving semantic and syntactic ambiguity b) Parsing sentences into morphemes c) Identifying word boundaries d) Tokenizing text into characters 99) Which of the following is a measure of similarity between two sentences? a) Cosine similarity b) Syntactic dependency c) Parse tree depth d) Transition probability 100) What is semantic entailment in NLP? a) One sentence logically follows from another b) Words have similar meanings c) Words have opposite meanings d) Syntactic structures are resolved