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What is the study of morphology in NLP?
What is the study of morphology in NLP?
What is a morpheme?
What is a morpheme?
Which of these is a derivational morpheme?
Which of these is a derivational morpheme?
Which of these is a free morpheme?
Which of these is a free morpheme?
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What is stemming used for?
What is stemming used for?
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Which NLP task often relies on morphological parsing?
Which NLP task often relies on morphological parsing?
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What does a parse tree represent?
What does a parse tree represent?
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Which of the following is an example of inflectional morphology?
Which of the following is an example of inflectional morphology?
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What is the main purpose of tokenization in NLP?
What is the main purpose of tokenization in NLP?
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What is a context-free grammar (CFG)?
What is a context-free grammar (CFG)?
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What is syntactic ambiguity?
What is syntactic ambiguity?
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What is a probabilistic context-free grammar (PCFG)?
What is a probabilistic context-free grammar (PCFG)?
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"I saw bats" contains which type of ambiguity?
"I saw bats" contains which type of ambiguity?
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The words "bank/data bank/blood bank" is an example of _______________.
The words "bank/data bank/blood bank" is an example of _______________.
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HMM are designed to model the joint distribution P(H, O), where H is the ________ state and O is the ________ state.
HMM are designed to model the joint distribution P(H, O), where H is the ________ state and O is the ________ state.
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Elements of Semantic analysis
Elements of Semantic analysis
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Which of the following is an example of irregular noun form?
Which of the following is an example of irregular noun form?
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What is the role of syntactic analysis in NLP?
What is the role of syntactic analysis in NLP?
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_______________ morphology is a type of word formation that creates new lexemes.
_______________ morphology is a type of word formation that creates new lexemes.
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Which approach to WSD uses dictionaries or thesauri?
Which approach to WSD uses dictionaries or thesauri?
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What is syntactic structure used for in NLP?
What is syntactic structure used for in NLP?
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What is the primary challenge of syntactic analysis?
What is the primary challenge of syntactic analysis?
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Which NLP task is primarily concerned with analyzing sentence structure?
Which NLP task is primarily concerned with analyzing sentence structure?
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What is syntactic analysis?
What is syntactic analysis?
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Which type of representation is used in syntactic analysis?
Which type of representation is used in syntactic analysis?
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Which term describes words that have the same spelling but different meanings?
Which term describes words that have the same spelling but different meanings?
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What is the goal of semantic parsing?
What is the goal of semantic parsing?
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Which algorithm is used for parsing sentences in CFG?
Which algorithm is used for parsing sentences in CFG?
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What does statistical parsing rely on?
What does statistical parsing rely on?
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Which parsing technique uses probabilities to select the most likely parse tree?
Which parsing technique uses probabilities to select the most likely parse tree?
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Which component of HMM represents transitions between states?
Which component of HMM represents transitions between states?
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What type of grammar is used in syntactic analysis?
What type of grammar is used in syntactic analysis?
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What is a top-down parsing algorithm?
What is a top-down parsing algorithm?
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What are the two components of FST?
What are the two components of FST?
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What is bottom-up parsing?
What is bottom-up parsing?
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What is the difference between statistical parsing and rule-based parsing?
What is the difference between statistical parsing and rule-based parsing?
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What is a dependency tree?
What is a dependency tree?
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What is head-dependent structure in syntactic analysis?
What is head-dependent structure in syntactic analysis?
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What is the difference between lemmatization and stemming?
What is the difference between lemmatization and stemming?
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What is a collocation in NLP?
What is a collocation in NLP?
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What is dependency parsing used for?
What is dependency parsing used for?
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What is lexical semantics?
What is lexical semantics?
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What is Word Sense Disambiguation (WSD)?
What is Word Sense Disambiguation (WSD)?
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Which of the following is NOT a feature of lexical semantics?
Which of the following is NOT a feature of lexical semantics?
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What is the output of lemmatization?
What is the output of lemmatization?
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What is Latent Semantic Analysis (LSA)?
What is Latent Semantic Analysis (LSA)?
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What does semantic analysis in NLP focus on?
What does semantic analysis in NLP focus on?
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Which of these represents relations among lexemes?
Which of these represents relations among lexemes?
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What is semantic role labeling?
What is semantic role labeling?
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Which approach does LSA primarily rely on?
Which approach does LSA primarily rely on?
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What is a corpus in POS tagging?
What is a corpus in POS tagging?
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What is semantic similarity?
What is semantic similarity?
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What is the purpose of a feature extraction step in NLP?
What is the purpose of a feature extraction step in NLP?
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Which type of morpheme conveys grammatical information?
Which type of morpheme conveys grammatical information?
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What is the challenge in machine translation systems?
What is the challenge in machine translation systems?
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Which of the following is a measure of similarity between two sentences?
Which of the following is a measure of similarity between two sentences?
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What is semantic entailment in NLP?
What is semantic entailment in NLP?
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What does HMM stand for in POS tagging?
What does HMM stand for in POS tagging?
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What type of morpheme cannot stand alone?
What type of morpheme cannot stand alone?
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Study Notes
Morphology in NLP
- Morphology in natural language processing (NLP) is the study of word structure
- It focuses on how words are formed from smaller units called morphemes
- Morphemes are the smallest meaningful units of language
- Inflectional morphemes change the form of a word to indicate grammatical properties like tense or number
- Derivational morphemes create new words by changing the word class or meaning
- Free morphemes have independent meaning
- Bound morphemes must combine with other morphemes to have meaning
Morphemes
- Morphemes are the smallest meaningful units of a word
- Derivational morphemes modify the meaning or grammatical class of a word
- Free morphemes like "dog" have an independent meaning
- Bound morphemes, like "-ed" in "walked," need to combine with other morphemes to carry meaning
Stemming
- Stemming reduces inflected words to their root form
- This is used for grouping similar words together for tasks in NLP
- This process simplifies word forms and is generally faster than the alternative approach
NLP Tasks
- Part-of-speech (POS) tagging involves identifying the grammatical role of words in a sentence
- Morphological parsing involves breaking down words into their morphological components
- Semantic analysis focuses on the meaning of words and sentences in a language
- Syntactic analysis focuses on the grammatical structure of sentences
CFG and PCFG
- Context-Free Grammars (CFG) are sets of rules describing how to build syntactically valid sentences
- Probabilistic Context-Free Grammars (PCFG) extend CFGs by associating probabilities with productions rules.
- PCFGs are used to model the likelihood of different syntactic structures in natural language
- These models are essential for automatic parsing.
Ambiguity
- Ambiguity: A sentence can have multiple possible meanings or interpretations.
- Syntactic ambiguity: A sentence can have more than one possible syntactic structure.
- Lexical ambiguity: A word can have more than one meaning
Dependency Parsing
- Dependency parsing identifies the grammatical relationships between words in a sentence
- These relationships are represented using directed acyclic graphs, where words are nodes and relationships are directed edges
- Dependency parsing is a vital tool for automatic sentence structure analysis
Word Sense Disambiguation (WSD)
- Aims to determine the correct sense of a word in a given context.
Semantic Role Labeling
- Semantic role labeling (SRL) is a technique that identifies the role of each word in a sentence, in relation to the main verb.
- E.g. who performed the action, what was the object
- This is very important for many applications of natural language processing (NLP).
Parse Trees
- Parse trees are graphical representations of a sentence's grammatical structure.
- They depict how words and phrases in a sentence combine based on syntactic rules
- Parse trees aid in determining the grammatical relationships among words in a sentence
Semantic Similarity
- Measures the similarity in meaning between two words, phrases or sentences.
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Description
Explore the concepts of morphology and morphemes in natural language processing (NLP). This quiz covers the formation of words from morphemes, including inflectional and derivational types, as well as the process of stemming. Test your understanding of these fundamental aspects of NLP.