Wordnet Introduction
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Transcript of Wordnet Introduction
WORDNET Reporter: Nguyen Duc Minh Khoi
@ Ho Chi Minh City University of Technology
Thursday, November 01, 2012
Contents
Intro to WordNet
Nouns
Modifiers
Verbs
WordNet system
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INTRODUCTION TO WORDNET
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Overview
• WordNet is lexical database for the English language that groups English word into set of synonyms called synset
• Authors: the Cognitive Science Laboratory of Princeton University under the direction of psychology professor George A. Miller
• Used by: • Linguistics Scientist
• Psychologist
• Artificial intelligence Scientist
• Natural Language Processing Scientist
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Contents of WordNet
• WordNet distinguish between nouns, verbs, adjectives, adverbs – 4 major syntactic categories
• WordNet contains basic units: • Compounds
• Phrasal verbs
• Collocations
• Idiomatic phrases
• WordNet as a dictionary: • Give definitions
• Sample sentences
• Contains synonym sets
• WordNet as a thesaurus: • Conceptual level: semantic conceptual relations
• Lexical level: lexical relation
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Other information
• Lexical database can be built by: • Automatic acquisition
• Craft one dictionary by hand
• Knowledge engineering: • Lexical level: contains information about synonyms, antonyms...
• Domain level: refer to the topic of discourse
• Application specific level: relates objects and events
• Tennis problem: • Contains no relations that indicate the word’s shared membership in a
topic of discourse
• E.g. not link racquet, ball, net => court game
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NOUNS
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Introduction to nouns in WordNet
• WordNet is machine readable dictionary
• Noun in WordNet doesn’t give: • pronunciation
• Derivative morphology
• Etymology
• Usage notes
• Pictorial illustration
• WordNet try to make semantic relations by extract synonym from thesaurus manually
• WordNet lexicalized concept by making synset relate to that concept
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Lexical hierarchy
• Tree graph: graph without circular loop
• Assumptions: • Longer distance in hierarchy longer traverse in thoughts
• More lexical information must be stored in every lexicalized concepts than is required to establish in hierarchy.
• Noun’s unique beginner:
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Lexical hierarchy (cont.)
• Examples:
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Noun relations • Hyponyms (~):
• A word of more specific meaning than a general or superordinate term applicable to it.
• For example, {bowl} is a hyponym of {dish}: {bowl} ~-> {dish}
• Hypernyms (@): • A word with a broad meaning that more specific words fall under; a
superordinate.
• For example, {color} is a hypernym of {red}: {color} @-> {red}
• Meronyms (#): • The semantic relation that holds between a part and the whole.
• For example, {beak} and {wing} are meronyms of {bird}: {beak, wing} #-> bird
• Three kinds: component, member, made from
• Holonyms (%): • The semantic relation that holds between a whole and its parts
• For example, {building} is a holonym of {window}: {building} %-> {window}
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Noun relations (cont.)
• Antonyms (!): • A word opposite in meaning to another
• For example, {man} !-> {woman}
• Polysemous nouns: • Nous that have many meanings
• For example, {mouse} living animal or computer device
• Rules: two meanings of a word are similar then the meaning of their hyponyms should also be similar in the same way.
• Attribute (=) and modifications: • Values of attribute are expressed by adjectives
• Modification can also be nouns
• For examples, chair -> small chair, big chair
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MODIFIERS
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Adjectives
• Main functions: modifying nouns
• Types: • Descriptive adjectives
• Participle adjectives
• Relational adjectives
• Format: • A(x) = adj
• E.g.: WEIGHT(package) = heavy
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Adjectives Relations • Antonyms (!):
• Basic semantic relation among descriptive adjectives
• Means “IS ANOYNYMOUS TO”, e.g. heavy is anonymous to light
• Can be direct, e.g. heavy/light
• Or can be indirect, e.g. heavy/airy
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Adjectives Relations (cont.)
• Other relations • Troponym (~):
• Hypernym (@):
• Entailment (*):
• Cause (>):
• Also see (^):
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Gradation
• Contrary: one of propositions can be true or both are false
• Adjectives can be use to express different level of action
• For example:
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Other stuffs
• Markedness: • Normal linguistic unit (unmarked term) compare to unit possible
irregular forms (marked term)
• E.g.: The pool is 5 feet deep, NOT: The pool is 5 feet shallow
• So deep marked term, shallow unmarked term
• Polysemy and selectional preferences: • E.g.: old can be not young modify persons
old can be not new modify things
• Some adjectives can modify almost any nouns
• E.g.: good / bad, desirable / undesirable
• Some adjectives can strictly restricted to some nouns
• E.g.: editable / ineditable
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Other types of descriptive adjectives
• Color adjectives: • Server as nouns and adjectives
• Quantifiers: • E.g.: all, some, many, few…
• Participle adjectives: • Means “PRINCIPLE PART OF”
• E.g.: breaking is principle part of break
• Can be –ing/-ed: running water, elapsed time
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Relational adjectives
• Differ from descriptive adjectives by • Do not relate to attribute of nouns
• Can not be gradable
• Occur only attribute position
• Lack of direct antonym
• E.g.: criminal behavior
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Adverbs
• Derived from adjectives by suffixation: • -ly:
• Specify manner: e.g.: beautifully
• Specify degree: e.g.: extremely
• Other suffix:
• -wise, -way, -ward
• E.g.: northward, forward
• Inherit their adjectives about: • Antonym
• Gradation
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VERBS
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Organizations
• Types of semantic verbs: • motion, perception, communication, competition, change, cognitive,
consumption, creation, emotion, possession, body care, functions, social behavior, interaction.
• Stative verb: • Collaborate with be: resemble, belong, suffice
• Control verb: want, fail, prevent, succeed, begin
• Cannot group all verbs in unique beginner like nouns
• English has fewer verb than nouns BUT approximate twice as polysemous as noun
• Verb synset: • Synonym and near synonym: e.g.: pass away vs. die vs. kick the bucket
• Idiom and metaphors: • Kick the bucket include synset
• Die include synonym: break, break down (for car and computer)
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Verb Relations
• Entailment (*): • The verb Y is entailed by X if by doing X you must be doing Y
• E.g.: to snore entails to sleep
• Not mutual: V1 * V2 NOT V2 V1
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Verb relations
• Troponym (~): • The verb Y is a troponym of the verb X if the activity Y is doing X in
some manner
• E.g.: to lisp is a troponym of to talk
• Special case of entailment
• Most frequently coded in WordNet
• Antonym (!): • E.g.: give/take, buy/sell, lend/borrow, teach/learn
• Can also be troponym: fail/succeed entails try, forget entails know
• Hypernym (@): • The verb Y is a hypernym of the verb X if the activity X is a (kind of) Y
• E.g.: to perceive is an hypernym of to listen
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WORDNET SYSTEM
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WordNet system
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Lexical files
• WordNet store nouns, adjectives, adverbs and nouns into synset lexical source files by syntactic categories • Nouns and verbs: grouped according to semantic fields
• Adjectives are divided among three files (adj.all, adj.ppl, adj.pert)
• Adverb are store in single file
• Relation pointers store in WordNet
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Sample Application use WordNet
• NLTK is a platform for building Python programs to work with human language data
• Sample commands: • Work with nouns:
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Sample Application use WordNet (cont.)
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• Work with verbs