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61A Lecture 35 Wednesday, December 4 Announcements 2 - PowerPoint PPT Presentation

Oct 16, 2023 •207 likes •1.4k views

61A Lecture 35 Wednesday, December 4 Announcements 2 Announcements Homework 11 due Thursday 12/5 @ 11:59pm. 2 Announcements Homework 11 due Thursday 12/5 @ 11:59pm. No video of lecture on Friday 12/6. 2 Announcements Homework

  1. Machine Translation Target language corpus gives examples of well-formed sentences I will get to it later He will do it See you later Parallel corpus gives translation examples I will do it gladly You will see later Yo lo haré de muy buen grado Después lo veras 7

  2. Machine Translation Target language corpus gives examples of well-formed sentences I will get to it later He will do it See you later Parallel corpus gives translation examples I will do it gladly You will see later Yo lo haré de muy buen grado Después lo veras Machine translation system: 7

  3. Machine Translation Target language corpus gives examples of well-formed sentences I will get to it later He will do it See you later Parallel corpus gives translation examples I will do it gladly You will see later Yo lo haré de muy buen grado Después lo veras Machine translation system: Model of translation 7

  4. Machine Translation Target language corpus gives examples of well-formed sentences I will get to it later He will do it See you later Parallel corpus gives translation examples I will do it gladly You will see later Yo lo haré de muy buen grado Después lo veras Machine translation system: Source language Target language Model of Yo lo haré después I will do it later translation N OVEL S ENTENCE 7

  5. Syntactic Agreement in Translation S S NP VP NP VP MD VP MD VP PRP VB PRP ADV PRP VB ADV I will do it gladly You will see later Yo lo haré de muy buen grado Después lo veras Machine translation system: Model of Yo lo haré después I will do it later translation 8

  6. Syntactic Agreement in Translation S S NP VP NP VP MD VP MD VP PRP VB PRP ADV PRP VB ADV I will do it gladly You will see later Yo lo haré de muy buen grado Después lo veras Machine translation system: ADV ADV Model of Yo lo haré después I will do it later translation 8

  7. Syntactic Agreement in Translation S S NP VP NP VP MD VP MD VP PRP VB PRP ADV PRP VB ADV I will do it gladly You will see later Yo lo haré de muy buen grado Después lo veras Machine translation system: S S ADV ADV Model of Yo lo haré después I will do it later translation 8

  8. Syntactic Agreement in Translation S S NP VP NP VP MD VP MD VP PRP VB PRP ADV PRP VB ADV I will do it gladly You will see later Yo lo haré de muy buen grado Después lo veras Machine translation system: S S ADV ADV Model of Yo lo haré después I will do it later translation 8

  9. Syntactic Reordering in Translation pair added to the lexicon 9

  10. Syntactic Reordering in Translation S VP PP NP NP NN VBD TO DT NN pair added to the lexicon 9

  11. Syntactic Reordering in Translation S S VP PP NP NP NP NN VBD TO DT NN NN pair added to the lexicon pair 9

  12. Syntactic Reordering in Translation S S VP VP PP NP NP NP NN VBD TO DT NN NN VBD pair added to the lexicon pair added 9

  13. Syntactic Reordering in Translation S S VP VP PP PP NP NP NP NN VBD TO DT NN NN TO VBD pair added to the lexicon pair to added 9

  14. Syntactic Reordering in Translation S S VP VP PP PP NP NP NP NP NN VBD TO DT NN NN DT NN TO VBD pair added to the lexicon pair to added the lexicon 9

  15. Syntactic Reordering in Translation S S VP VP PP PP NP NP NP NP NN VBD TO DT NN NN DT NN TO VBD pair added to the lexicon pair to added the lexicon 9

  16. Syntactic Reordering in Translation S S VP VP PP PP NP NP NP NP NN VBD TO DT NN NN DT NN TO VBD pair added to the lexicon pair to added the lexicon 9

  17. Syntactic Reordering in Translation S S VP VP PP PP NP NP NP NP NN VBD TO DT NN NN DT NN TO VBD pair added to the lexicon pair to added the lexicon 9

  18. Syntactic Reordering in Translation S S VP VP PP PP NP NP NP NP NN VBD TO DT NN NN DT NN TO VBD pair added to the lexicon pair to added the lexicon 9

  19. 一対 が Syntactic Reordering in Translation S S VP VP PP PP NP NP NP NP NN VBD TO DT NN NN DT NN TO VBD pair added to the lexicon pair to added the lexicon pair 9

  20. 目録 一対 が Syntactic Reordering in Translation S S VP VP PP PP NP NP NP NP NN VBD TO DT NN NN DT NN TO VBD pair added to the lexicon pair to added the lexicon pair list 9

  21. に 目録 一対 が Syntactic Reordering in Translation S S VP VP PP PP NP NP NP NP NN VBD TO DT NN NN DT NN TO VBD pair added to the lexicon pair to added the lexicon pair list to 9

  22. 一対 が 目録 追加 されました に Syntactic Reordering in Translation S S VP VP PP PP NP NP NP NP NN VBD TO DT NN NN DT NN TO VBD pair added to the lexicon pair to added the lexicon pair list to add was 9

  23. Context-Free Grammars

  24. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. 11

  25. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S 11

  26. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP S 11

  27. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP S NP VP 11

  28. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S NP VP 11

  29. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S NP VP PRP 11

  30. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S NP VP Lexicon PRP 11

  31. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S NP VP Lexicon PRP PRP -> I 11

  32. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S NP VP Lexicon PRP PRP -> I I 11

  33. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S VP -> VB NP VP Lexicon PRP PRP -> I I 11

  34. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S VP -> VB VP -> VB NP NP VP Lexicon PRP PRP -> I I 11

  35. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S VP -> VB VP -> VB NP NP VP Lexicon PRP VB NP PRP -> I I 11

  36. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S VP -> VB VP -> VB NP NP VP Lexicon PRP VB NP PRP -> I I VB -> know VB -> help 11

  37. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S VP -> VB VP -> VB NP NP VP Lexicon PRP VB NP PRP -> I I know VB -> know VB -> help 11

  38. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S VP -> VB VP -> VB NP NP VP Lexicon PRP VB NP PRP -> I I know PRP VB -> know VB -> help 11

  39. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S VP -> VB VP -> VB NP NP VP Lexicon PRP VB NP PRP -> I PRP -> you I know PRP VB -> know VB -> help 11

  40. A Context-Free Grammar Models Language Generation Grammar Rules A grammar contains rules that hierarchically generate word sequences using syntactic tags. S -> NP VP NP -> PRP S VP -> VB VP -> VB NP NP VP Lexicon PRP VB NP PRP -> I PRP -> you I know PRP VB -> know VB -> help you 11

  41. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP VP -> VB VP -> VB NP PRP Lexicon I PRP -> I PRP -> you VB -> know VB -> help 12

  42. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP VP -> VB VP -> VB NP PRP Lexicon I PRP -> I PRP -> you VB -> know VB -> help 12

  43. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP VP -> VB VP -> VB NP PRP VP -> MD VP Lexicon I PRP -> I PRP -> you VB -> know VB -> help 12

  44. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP VP -> VB VP -> VB NP PRP VP -> MD VP Lexicon I PRP -> I PRP -> you VB -> know VB -> help 12

  45. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP 0.2 VP -> VB VP -> VB NP 0.7 PRP 0.1 VP -> MD VP Lexicon I PRP -> I PRP -> you VB -> know VB -> help 12

  46. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP 0.2 VP -> VB VP -> VB NP 0.7 VP PRP MD 0.1 VP -> MD VP Lexicon I PRP -> I PRP -> you VB -> know VB -> help 12

  47. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP 0.2 VP -> VB VP -> VB NP 0.7 VP PRP MD 0.1 VP -> MD VP Lexicon I PRP -> I PRP -> you VB -> know VB -> help MD -> can 12

  48. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP 0.2 VP -> VB VP -> VB NP 0.7 VP PRP MD 0.1 VP -> MD VP Lexicon I can PRP -> I PRP -> you VB -> know VB -> help MD -> can 12

  49. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP 0.2 VP -> VB VP -> VB NP 0.7 VP PRP MD 0.1 VP -> MD VP Lexicon I can PRP -> I PRP -> you VB -> know VB -> help MD -> can 12

  50. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP 0.2 VP -> VB VP -> VB NP 0.7 VP PRP MD 0.1 VP -> MD VP Lexicon I can VB NP PRP -> I PRP -> you help VB -> know VB -> help MD -> can 12

  51. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP 0.2 VP -> VB VP -> VB NP 0.7 VP PRP MD 0.1 VP -> MD VP Lexicon I can VB NP PRP -> I PRP -> you help PRP VB -> know VB -> help MD -> can 12

  52. Probabilistic Context-Free Grammars S Grammar Rules S -> NP VP NP -> PRP NP VP 0.2 VP -> VB VP -> VB NP 0.7 VP PRP MD 0.1 VP -> MD VP Lexicon I can VB NP PRP -> I PRP -> you help PRP VB -> know VB -> help you MD -> can 12

  53. Learning Probabilistic Context-Free Grammars (Demo)

  54. Parsing with Probabilistic Context-Free Grammars

  55. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. 15

  56. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow 15

  57. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow 15

  58. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow 15

  59. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow fruit flies like bananas 15

  60. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow fruit flies like bananas 15

  61. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow fruit flies like bananas 15

  62. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow fruit flies like bananas Parse by finding the tree with the highest total probability that yields the sentence. 15

  63. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow fruit flies like bananas Parse by finding the tree with the highest total probability that yields the sentence. Algorithm: Try every rule over every span. Match the lexicon to each word. 15

  64. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow fruit flies like bananas Parse by finding the tree with the highest total probability that yields the sentence. Algorithm: Try every rule over every span. Match the lexicon to each word. time flies like an arrow 0 1 2 3 4 5 15

  65. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow fruit flies like bananas Parse by finding the tree with the highest total probability that yields the sentence. Algorithm: Try every rule over every span. Match the lexicon to each word. S -> NP VP time flies like an arrow 0 1 2 3 4 5 15

  66. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow fruit flies like bananas Parse by finding the tree with the highest total probability that yields the sentence. Algorithm: Try every rule over every span. Match the lexicon to each word. S -> NP VP NP -> NN time flies like an arrow 0 1 2 3 4 5 15

  67. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow fruit flies like bananas Parse by finding the tree with the highest total probability that yields the sentence. Algorithm: Try every rule over every span. Match the lexicon to each word. S -> NP VP NP -> NN NN -> time time flies like an arrow 0 1 2 3 4 5 15

  68. Parsing is Maximizing Likelihood A probabilistic context-free grammar can be used to select a parse for a sentence. time flies like an arrow fruit flies like bananas Parse by finding the tree with the highest total probability that yields the sentence. Algorithm: Try every rule over every span. Match the lexicon to each word. S -> NP VP NP -> NN VP -> VBZ PP NN -> time time flies like an arrow 0 1 2 3 4 5 15

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