Natural Language Processing

1. Natural Language Processing Lecture Notes 9 Chapter 16 Lexical Semantics

2. Meaning • Individual words • Individual sentences/utterances (what’s the difference?) • Discourse/dialog(ue)

3. Lexicon • Lexemes (basic unit) • Lexical semantics: • Relations among word meanings • Internal structure

4. Lexemes • Form: particular orthographic and phonological form (what do these mean?) • Sense: a symbolic meaning representation; may be a set of related senses (WordNet)

5. Dictionary Definitions • red, n: the color of blood or a ruby • Blood, n: the red liquid that circulates in the heart, arteries and veins of animals • Above refer to each other! • Right, adj: located nearer the right hand esp. being on the right when facing the same direction as the observer • Uses the word being defined • Dictionary definitions don’t stand on their own; lexemes defined in terms of others • Useful if user know lots of other words • Also, need grounding in external world

6. Dictionaries • Even so, there is a lot of information in these definitions • Red is a color • Blood is a liquid • Red can be applied to blood • Applications can perform sophisticated semantic tasks given a large database of such facts – even thought they don’t really understand what the words *mean* • We can learn much semantics to support NLP by finding relationships between lexemes in various settings • Chapter 16: focuses on resources available to NLP apps that can benefit from knowledge of semantics

7. Lexical relations 1: Homonymy • Same form, unrelated meanings • A bank holds investments in a custodial account • Agriculture is burgeoning on the east bank • Prototypically, homonyms share both orthographic and phonological forms • Variants • Homophones – same pronunciation, different orthographic forms, unrelated meanings • Read, red • Homograph – same orthographic form, different pronunciation, unrelated meanings • Bass, bass

8. Challenges for NLP applications • Parsing and speech recognition: • All uses of ‘bank’ are conflated, even though different lexemes are used in different contexts. • Problem for, e.g., lexicalized grammars and n-gram prediction in speech • E.g., bank sense-3 may co-occur often with river, while sense-6 may co-occur often with money (and not river) • Subcategorizations may differ (especially frequency; bank the plane versus bank the dollar) • Text to speech • How should the system pronounce bass?

9. Polysemy • Multiple related meanings of a lexeme • May be difficult to distinguish from homonymy • In practice, may be treated the same in a lexicon (e.g., WordNet)

10. Bank in WordNet • S: (v) bank (tip laterally) "the pilot had to bank the aircraft" • S: (v) bank (enclose with a bank) "bank roads" • S: (v) bank (do business with a bank or keep an account at a bank) "Where do you bank in this town?" • S: (v) bank (act as the banker in a game or in gambling) • S: (v) bank (be in the banking business) • S: (v) deposit, bank (put into a bank account) "She deposits her paycheck every month" • S: (v) bank (cover with ashes so to control the rate of burning) "bank a fire" • S: (v) trust, swear, rely, bank (have confidence or faith in) "We can trust in God"; "Rely on your friends"; "bank on your good education"; "I swear by my grandmother's recipes"

11. Polysemy • They rarely serve red meat • He served as US ambassador • He might have served his time in prison • Look up serve in WordNet • Again, for contrast: • Homonymy: distinct and unrelated meanings, possibly with different etymology (multiple lexemes) • Polysemy: single lexeme with multiple related meanings; etymologically related (history, evolution)

12. Lexicon Creation • For a given lexeme, how can its senses be reliably distinguished? • Hard! Agreement among lexicographers is not high. Often, too many are proposed (by the “splitters” as opposed to the “lumpers”) • Tests: semantic roles, domains, actions, zeugma (combine using ‘and’) • WordNet entry for serve • Which of those flights serve breakfast? • Does USAir serve Pittsburgh? • He served as ambassador • 1 v. 2: same subcat, but different semantic roles • ProbBank entry for serve-v (2 is missing) • ? Does USAIR serve breakfast and Pittsburgh? (zeugma) • Different domains: food/service; flights/airlines (too specific?); positions/offices

13. Lexicon Creation • An interesting example • Diane went to NYC • Diane went to William and Mary • Change sense to make it make sense!

14. Metaphor and Metonymy • Both extend existing sense to new meaning • Metaphor: completely different concept • Metonymy: related concepts • Metaphor: • use words with meaning appropriate for a completely different kind of concept • That doesn’t scare digital – corporation as person • Father of the atom bomb – bomb as child • Novel versus conventional • Etc!

15. Metaphor and Metonymy • Metonymy • The ham sandwich wants his coffee • GM killed the Fiero (metonymy) • Metaphor? Perhaps a wordsense that involves metaphor; but probably not a metaphor that requires creative cognitive processing

16. Synonymy • Substitutability • How big is that plane? • How large is that plane? • If we require substitutability in ALL contexts, we won’t have many synonyms; we’ll settle for substitutable in some context • How big are you? (height or age) How large are you? (weight)

17. Synonymy • Compare: • A big fat apple • ? A large fat apple • A big sister • ? A large sister • Compare house/home • Influences: • Subtle shades of meaning • Polysemy (large versus old sense) • Register (social factors); casual, academic, royal, polite… (cheap versus parsimonious) • Collocational constraints (roast beef, ? Baked beef)

18. My AFS is messed up…lost my slides from yesterday afternoon…. • On the board: • Lexical relations in WordNet; Synsets • Thematic roles • Selectional restrictions, including using WordNet entries to define selectional restrictions • Ambiguity: e.g., prepare a dish vs. wash a dish: this sense of prepare takes a result that is food/nutrient makes it more likely that we have the food meaning of dish • Primitive Decomposition: Schank’s Conceptual Dependency