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Lecture

Lecture. Lexical Semantics. What is lexical semantics?. Meaning of Words Lexical Relations WordNet Thematic Roles Selectional Restrictions Conceptual Dependency. What is a word?. Lexeme: an entry in the lexicon that includes an orthographic representation a phonological form

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Lecture

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  1. Lecture Lexical Semantics CS 4705

  2. What is lexical semantics? • Meaning of Words • Lexical Relations • WordNet • Thematic Roles • Selectional Restrictions • Conceptual Dependency

  3. What is a word? • Lexeme: an entry in the lexicon that includes • an orthographic representation • a phonological form • a symbolic meaning representation or sense • Dictionary entries: • Red (‘red) n: the color of blood or a ruby • Blood (‘bluhd) n: the red liquid that circulates in the heart, arteries and veins of animals • Word Sense Disambiguation • For any given lexeme, how can its sense be reliably distinguished? • Lex. Rel. III: Metaphor, Metonymy • What is metaphor? • That doesn't scare Digital. • What is metonymy? • GM killed the Fiero. • Extension of existing sense to a new meaning. • Lexical Relations IV: Synonomy • What is synonomy? Substitutability. • How big is that plane? • How large is that plane? • Compare: • A big fat apple • ?A large fat apple • A big sister • ?A large sister • Influences on substitutability: • subtle shades of meaning differences • polysemy • register • collocational constraints • Lexical Relations V: Hyponomy • What is hyponomy? • General: hyponym • Specific: hypernym • Example: ``car'' is a hyponym of ``vehicle'' • and ``vehicle'' is a hypernym of ``car.'' • Test: ``That is a car'' implies ``That is a vehicle'' • What is ontology? • What is taxonomy? • What is object hierarchy? • %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% • Semantic Networks • Used to represent relationships between words • Example: WordNet - created by George Miller's team at Princeton • http://www.cogsci.princeton.edu/$\sim$wn • %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% • WordNet (1.6) • WordNet is the most widely used hierarchically organized lexical • database for English -- Fellbaum (1998). • \vspace{.1in • \epsfxsize=1\textwidth • \fig{\file{figures{fig16.01.ps • %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% • Format of WordNet Entries • WordNet sense entries consist of a set of synonyms, a dictionary-style • definition (or gloss), and some examples of uses. • \vspace{.1in • \epsfxsize=1\textwidth • \fig{\file{figures{fig16.02.ps • %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% • Sense Distribution for WordNet Verbs • \vspace{.1in • \epsfxsize=1\textwidth • \fig{\file{figures{fig16.03.ps • %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% • Lexical (N) Relations in WordNet • \vspace{.1in • \epsfxsize=1\textwidth • \fig{\file{figures{fig16.04.ps • %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% • Verb Relations in WordNet • \vspace{.1in • \epsfxsize=1\textwidth • \fig{\file{figures{fig16.05.ps • %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% • Adj. and Adv. Relations in WordNet • \vspace{.1in • \epsfxsize=1\textwidth • \fig{\file{figures{fig16.06.ps • %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% • Synsets in WordNet • WordNet is organized around the notion of synset. • { chump, fish, fool, gull, mark, patsy, fall guy, sucker, schlemiel, • shlemiel, soft touch, mug } • Important: It is this exact synset that makes up one of the sense for • each of the entries listed in the synset. • Theoretically, each synset can be viewed as a concept in a taxonomy -- • like the concepts described in Chapter 14. • Hyponomy in WordNet • fig16.07.ps • Internal Structure of Words • What are the meaning components underlying word sense? • Thematic Roles (theta-roles) • What is a thematic role? • E w,x,y,z Giving (x) ^ Giver(w,x) ^ Givee(z, x) • ^ Given(y,x) $ • E w,x,z Breaking (x) ^ Breaker(w,x) ^ Broken(z,x) • Generic Thematic Roles • fig16.08.ps • Examples of Thematic Roles • fig16.09.ps • Early Theories of Thematic Roles • 1967-1968: "The beginning of Lexical Semantics" (Fillmore; Gruber; • Jackendoff (based on Gruber)) • Two fundamentally different approaches to linguistics • Gruber/Jackendoff: account for semantics and use grammar derived to say • something about syntax • Fillmore: account for syntax and use that to describe semantics • Thematic Level • Why posit a thematic level distinct from that of syntactic • subcategorization? • capture similarity between different (but related) uses of same • lexical item) • obviate need for subcategorization frames: mapping from syntax to • lexical semantics • Selectional Restrictions • What are selectional restrictions? • Recall the "Godzilla" example. • Selectional Restriction Implementation • A WordNet approach: hamburgers are edible • fig16.10.ps • Primitive Decomposition • Jim killed his philodendron • Jim did something to cause his philodendron to become not alive • Schank's Primitives • Conceptual Dependency • fig16.11.ps • Pred. Independence vs. Dependence • Predicate-Independent • single set of roles is chosen independent of the type of predicates involved (no reference to • type of predicates) • Schank • Predicate-Dependent • roles identified by particular positions arguments • occupy with respect to primitive predicates • Decomposition vs. Non-Decomposition • Decomposition / Compositional Approach (Schank, Jackendoff) vs. • Non-decomposition / Noncomposition Approach (Fillmore) • Within compositional approaches: exhaustive (Schank) vs. nonexhaustive • (Jackendoff) • Schank: Motivation • Underlying Motivation: "Strong AI" • Focus: understanding. Argues that the representation is reversible. • Rejects syntax during analysis. Allows it during generation. • Attempts to come up with well-defined system of rules and • conceptualizations. • Inferences, expectation, syntax, conversational norms, real world. • Conceptual Structure (CD): Language-independent conceptual level. • Schank: Kill vs. Die • Schank: Problem 1 • "John caused Mary to die" vs. "John killed Mary" • Identically substitutable? • Flaw of all compositional approaches of this nature. • Schank: Problem 2 • The decompositions are very complex. • Too specific • Why are these conceptualizations so radically distinct from the • syntactic realization? • Talks CD from NL understanding point of view -what about generation? • The NLP Bottleneck • Acquisition of Computational Lexicons • For Next Time • Chapter 18

  4. Right (‘rt) adj: located nearer the right hand esp. being on the right when facing the same direction as the observer • Left (‘left) adj: located nearer to this side of the body than the right • Do dictionaries give us definitions? • Some are circular • All are defined in terms of other lexemes • You have to know something to learn something • What can we learn from dictionaries? • Relations between words: • Oppositions, similarities, hierarchies

  5. Homonomy • Homonyms: Words with same form but different, unrelated meanings, or senses (multiple lexemes) • A bank holds investments in a custodial account in the client’s name. • As agriculture is burgeoning on the east bank, the river will shrink even more • Word sense disambiguation: what clues? • Similar phenomena • homophones - read and red (different orth. form) • homographs - bass and bass (different phon. form)

  6. Ambiguity: Which applications will these cause problems for? • General semantic interpretation • Machine translation • Spelling correction • Speech recognition • Text to speech • Information retrieval

  7. What is polysemy? • Word with multiple but related meanings (same lexeme) • They rarely serve red meat. • He served as U.S. ambassador. • He might have served his time in prison. • What’s the difference between polysemy and homonymy? • Homonymy: • Distinct, unrelated meanings • Different etymology? Coincidental similarity?

  8. Polysemy: • Distinct but related meanings • idea bank, sperm bank, blood bank, bank bank • How different? • Different subcategorization frames? • Domain specificity? • Zeugma: Can the two candidate senses be conjoined? ?He served his time and as ambassador to Norway. • For either, practical task: • What are its senses? (related or not) • How are they related? (polysemy ‘easier’ here) • How can we distinguish them?

  9. Metaphor, Metonymy • What is metaphor? • Father of the atom bomb. • What is metonymy? • GM killed the Fiero. • The ham sandwich wants his check. • Both extend existing sense to new meaning • Metaphor: use completely different concept (but cf conventional metaphors like GM) • Metonymy: use related concepts

  10. Synonomy • Substitutability: different lexemes with the same meaning • How big is that plane? • How large is that plane? • How big are you? Big brother is watching. • What influences substitutability? • Polysemy (large vs. old sense) • register: He’s really cheap/?parsimonious. • collocational constraint: roast beef, ?baked beef • convention: economy fare/?price

  11. Hyponomy • General: hypernym (super…ordinate) • dog is a hypernym of poodle • Specific: hyponym (under..neath) • poodle is a hyponym of dog • Test: That is a poodle implies that is a dog • What is ontology? Object in some domain • What is taxonomy? Structuring of those objects • What is object hierarchy? Structured hierarchy that supports feature inheritance

  12. Semantic Networks • Used to represent lexical relationships • e.g. WordNet (George Miller et al) • http://www.cogsci.princeton.edu/~wn • Most widely used hierarchically organized lexical database for English • Synset: set of synonyms, a dictionary-style definition (or gloss), and some examples of uses --> a concept • Databases for nouns, verbs, and modifiers • Applications can traverse network to find synonyms, antonyms, hierarchies,...

  13. Is a rock edible? • What are the parts of a human body? • What is a cheeseburger? • What are its parts? • What is the opposite of ambitious?

  14. Thematic Roles • E w,x,y,z Giving (x) ^ Giver(w,x) ^ Givee(z, x) • ^ Given(y,x) • E w,x,z Breaking (x) ^ Breaker(w,x) ^ Broken(z,x) • A set of roles: • agent, experiencer, force, theme, result, content, instrument, beneficiary, source, goal,... The dog ate the cheeseburger. What is cheeseburger? The sniper shot his victim with a rifle. What is rifle?

  15. Why do we need a thematic level? • We already have syntactic subcategorization • Capture similarity between different (but related) uses of same lexical item) • Avoid need for subcategorization frames: mapping from syntax to lexical semantics

  16. What are Selectional Restrictions? George ate a cheeseburger/his lunch/dirt. Jim killed his philodendron ?His philodenron killed Jim. The flu killed Jim.

  17. Schank's Conceptual Dependency • Eleven predicate primitives represent all predicates • Objects decomposed into primitive categories and modifiers • But few predicates result in very complex representations of simple things Ex,y Atrans(x) ^ Actor(x,John) ^ Object(x,Book) ^ To(x,Mary) ^ Ptrans(y) ^ Actor(y,John) ^ Object(y,Book) ^ To(y,Mary) John caused Mary to die vs. John killed Mary

  18. Next time • Word sense disambiguation and information retrieval • Chapter 17

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